Seeking for C9010-022 boot camp that performs great in real test?

killexams.com furnishes most current and 2022 current C9010-022 real questions with Exam Braindumps Questions and even Answers for fresh matters of IBM C9010-022 Test. Practice our C9010-022 VCE Inquiries and Answers to be able to Improve your comprehension and pass your current test with Substantial Marks. We assurance your success inside the Test Centre, covering all typically the references of test and developing your current Familiarity with the C9010-022 test. Pass with the C9010-022 boot camp.

Exam Code: C9010-022 Practice exam 2022 by Killexams.com team
C9010-022 IBM AIX Administration V1

Exam Title : IBM Certified System Administrator - AIX V1
Exam ID : C9010-022
Exam Duration : 120 mins
Questions in exam : 62
Passing Score : 36 / 62
Official Training : AIX Users and System Administration training path
Exam Center : Pearson VUE
Real Questions : IBM AIX Administration Real Questions
VCE practice exam : IBM C9010-022 Certification VCE Practice Test

System Availability
- Identify resources used by Cluster Aware AIX.
- Configure dump devices and analyze output.
- Determine elements necessary to reduce single points of failure, e.g. RAID, redundant hardware.
- Maintain hardware and CEC firmware (deferred/concurrent, etc.); replace, maintain, or install adapters; use ASMI. 9%
Storage Management
- Create and manage filesystems including extend, reduce, set and change attributes, etc..
- Create and manage logical volumes including extend, reduce, set and change attributes, etc.
- Create and manage volume groups including extend, reduce, set and change attributes, etc.
- Manage physical and virtual devices including multipathing.
- Manage storage devices (traditional disk, Solid State Drives, and tape) including redundancy (RAID). 15%
System and Network Security
- Configure role-based access control.
- Configure and manage remote access, e.g. ssh, SFTP, rlogin, etc.
- Manage system authentication grammar.
- Describe PowerSC components (basic understanding). 9%
Partition Management
- Configure and manage Logical Partitions (LPARs) including DLPAR operations.
- Create and manage Workload Partitions (WPAR) including Versioned WPARs and planning for Live Application Mobility.
- Understand HMC and IVM interfaces.
- Interact with and collect information from VIO servers (NOT VIO server technical focus; using and accessing virtual devices).
- Understand and explain LPAR and WPAR migration and mobility at a basic level. 12%
Performance Management and Tuning
- Use performance monitoring tools and plan for future growth.
- Analyze output from performance monitoring tools, e.g. iostat, vmstat, lparstat, Hot File Detection, and nmon.
- Configure system tunables to support optimal application performance, e.g. no, vmo, etc. 10%
Network Management
- Configure network devices including Etherchannel and Ipv4.
- Troubleshoot network issues.
- Configure TCP/IP with and without VLAN support.
- Configure NFS. 11%
System Management
- Create, maintain and modify user accounts.
- Manage services and subsystems using chtcp, etc.
- Configure the system and device attributes.
- Describe components of NIM.
- Install, apply, commit, or reject software.
- Create and manage paging space (aside from just the create and manage aspects, also PD aspects in cases where paging is exhausted).
- Use Cron and At. 13%
Install and Manage AIX
- Understand and manage AIX instance startup (boot process, maintenance mode, inittab, etc.).
- Backup and restore AIX.
- Install and manage WPARs.
- Install AIX and use NIM environments. 13%
General Administrative Tasks
- Create and use ksh and Perl scripts at a basic level.
- Use AIX commands such as TAR, CPIO, DD, RPM, SAVEVGSTRUC, and explain their use.
- Describe use of SNAP, particularly with support issues. 8%

IBM AIX Administration V1
IBM Administration techniques
Killexams : IBM Administration techniques - BingNews https://killexams.com/pass4sure/exam-detail/C9010-022 Search results Killexams : IBM Administration techniques - BingNews https://killexams.com/pass4sure/exam-detail/C9010-022 https://killexams.com/exam_list/IBM Killexams : IBM Research Rolls Out A Comprehensive AI And Platform-Based Edge Research Strategy Anchored By Enterprise Use Cases And Partnerships

I recently met with Dr. Nick Fuller, Vice President, Distributed Cloud, at IBM Research for a discussion about IBM’s long-range plans and strategy for artificial intelligence and machine learning at the edge.

Dr. Fuller is responsible for providing AI and platform–based innovation for enterprise digital transformation spanning edge computing and distributed cloud management. He is an IBM Master Inventor with over 75 patents and co-author of 75 technical publications. Dr. Fuller obtained his Bachelor of Science in Physics and Math from Morehouse College and his PhD in Applied Physics from Columbia University.

Edge In, not Cloud Out

In general, Dr. Fuller told me that IBM is focused on developing an "edge in" position versus a "cloud out" position with data, AI, and Kubernetes-based platform technologies to scale hub and spoke deployments of edge applications.

A hub plays the role of a central control plane used for orchestrating the deployment and management of edge applications in a number of connected spoke locations such as a factory floor or a retail branch, where data is generated or locally aggregated for processing.

“Cloud out” refers to the paradigm where cloud service providers are extending their cloud architecture out to edge locations. In contrast, “edge in” refers to a provider-agnostic architecture that is cloud-independent and treats the data-plane as a first-class citizen.

IBM's overall architectural principle is scalability, repeatability, and full stack solution management that allows everything to be managed using a single unified control plane.

IBM’s Red Hat platform and infrastructure strategy anchors the application stack with a unified, scalable, and managed OpenShift-based control plane equipped with a high-performance storage appliance and self-healing system capabilities (inclusive of semi-autonomous operations).

IBM’s strategy also includes several in-progress platform-level technologies for scalable data, AI/ML runtimes, accelerator libraries for Day-2 AI operations, and scalability for the enterprise.

It is an important to mention that IBM is designing its edge platforms with labor cost and technical workforce in mind. Data scientists with PhDs are in high demand, making them difficult to find and expensive to hire once you find them. IBM is designing its edge system capabilities and processes so that domain experts rather than PhDs can deploy new AI models and manage Day-2 operations.

Why edge is important

Advances in computing and storage have made it possible for AI to process mountains of accumulated data to provide solutions. By bringing AI closer to the source of data, edge computing is faster and more efficient than cloud. While Cloud data accounts for 60% of the world’s data today, vast amounts of new data is being created at the edge, including industrial applications, traffic cameras, and order management systems, all of which can be processed at the edge in a fast and timely manner.

Public cloud and edge computing differ in capacity, technology, and management. An advantage of edge is that data is processed and analyzed at / near its collection point at the edge. In the case of cloud, data must be transferred from a local device and into the cloud for analytics and then transferred back to the edge again. Moving data through the network consumes capacity and adds latency to the process. It’s easy to see why executing a transaction at the edge reduces latency and eliminates unnecessary load on the network.

Increased privacy is another benefit of processing data at the edge. Analyzing data where it originates limits the risk of a security breach. Most of the communications between the edge and the cloud is then confined to such things as reporting, data summaries, and AI models, without ever exposing the raw data.

IBM at the Edge

In our discussion, Dr. Fuller provided a few examples to illustrate how IBM plans to provide new and seamless edge solutions for existing enterprise problems.

Example #1 – McDonald’s drive-thru

Dr. Fuller’s first example centered around Quick Service Restaurant’s (QSR) problem of drive-thru order taking. Last year, IBM acquired an automated order-taking system from McDonald's. As part of the acquisition, IBM and McDonald's established a partnership to perfect voice ordering methods using AI. Drive-thru orders are a significant percentage of total QSR orders for McDonald's and other QSR chains.

McDonald's and other QSR restaurants would like every order to be processed as quickly and accurately as possible. For that reason, McDonald's conducted trials at ten Chicago restaurants using an edge-based AI ordering system with NLP (Natural Language Processing) to convert spoken orders into a digital format. It was found that AI had the potential to reduce ordering errors and processing time significantly. Since McDonald's sells almost 7 million hamburgers daily, shaving a minute or two off each order represents a significant opportunity to address labor shortages and increase customer satisfaction.

Example #2 – Boston Dynamics and Spot the agile mobile robot

According to an earlier IBM survey, many manufacturers have already implemented AI-driven robotics with autonomous decision-making capability. The study also indicated that over 80 percent of companies believe AI can help Strengthen future business operations. However, some companies expressed concern about the limited mobility of edge devices and sensors.

To develop a mobile edge solution, IBM teamed up with Boston Dynamics. The partnership created an agile mobile robot using IBM Research and IBM Sustainability Software AI technology. The device can analyze visual sensor readings in hazardous and challenging industrial environments such as manufacturing plants, warehouses, electrical grids, waste treatment plants and other hazardous environments. The value proposition that Boston Dynamics brought to the partnership was Spot the agile mobile robot, a walking, sensing, and actuation platform. Like all edge applications, the robot’s wireless mobility uses self-contained AI/ML that doesn’t require access to cloud data. It uses cameras to read analog devices, visually monitor fire extinguishers, and conduct a visual inspection of human workers to determine if required safety equipment is being worn.

IBM was able to show up to a 10X speedup by automating some manual tasks, such as converting the detection of a problem into an immediate work order in IBM Maximo to correct it. A fast automated response was not only more efficient, but it also improved the safety posture and risk management for these facilities. Similarly, some factories need to thermally monitor equipment to identify any unexpected hot spots that may show up over time, indicative of a potential failure.

IBM is working with National Grid, an energy company, to develop a mobile solution using Spot, the agile mobile robot, for image analysis of transformers and thermal connectors. As shown in the above graphic, Spot also monitored connectors on both flat surfaces and 3D surfaces. IBM was able to show that Spot could detect excessive heat build-up in small connectors, potentially avoiding unsafe conditions or costly outages. This AI/ML edge application can produce faster response times when an issue is detected, which is why IBM believes significant gains are possible by automating the entire process.

IBM market opportunities

Drive-thru orders and mobile robots are just a few examples of the millions of potential AI applications that exist at the edge and are driven by several billion connected devices.

Edge computing is an essential part of enterprise digital transformation. Enterprises seek ways to demonstrate the feasibility of solving business problems using AI/ML and analytics at the edge. However, once a proof of concept has been successfully demonstrated, it is a common problem for a company to struggle with scalability, data governance, and full-stack solution management.

Challenges with scaling

“Determining entry points for AI at the edge is not the difficult part,” Dr. Fuller said. “Scale is the real issue.”

Scaling edge models is complicated because there are so many edge locations with large amounts of diverse content and a high device density. Because large amounts of data are required for training, data gravity is a potential problem. Further, in many scenarios, vast amounts of data are generated quickly, leading to potential data storage and orchestration challenges. AI Models are also rarely "finished." Monitoring and retraining of models are necessary to keep up with changes the environment.

Through IBM Research, IBM is addressing the many challenges of building an all-encompassing edge architecture and horizontally scalable data and AI technologies. IBM has a wealth of edge capabilities and an architecture to create the appropriate platform for each application.

IBM AI entry points at the edge

IBM sees Edge Computing as a $200 billion market by 2025. Dr. Fuller and his organization have identified four key market entry points for developing and expanding IBM’s edge compute strategy. In order of size, IBM believes its priority edge markets to be intelligent factories (Industry 4.0), telcos, retail automation, and connected vehicles.

IBM and its Red Hat portfolio already have an established presence in each market segment, particularly in intelligent operations and telco. Red Hat is also active in the connected vehicles space.

Industry 4.0

There have been three prior industrial revolutions, beginning in the 1700s up to our current in-progress fourth revolution, Industry 4.0, that promotes a digital transformation.

Manufacturing is the fastest growing and the largest of IBM’s four entry markets. In this segment, AI at the edge can Strengthen quality control, production optimization, asset management, and supply chain logistics. IBM believes there are opportunities to achieve a 4x speed up in implementing edge-based AI solutions for manufacturing operations.

For its Industry 4.0 use case development, IBM, through product, development, research and consulting teams, is working with a major automotive OEM. The partnership has established the following joint objectives:

  • Increase automation and scalability across dozens of plants using 100s of AI / ML models. This client has already seen value in applying AI/ML models for manufacturing applications. IBM Research is helping with re-training models and implementing new ones in an edge environment to help scale even more efficiently. Edge offers faster inference and low latency, allowing AI to be deployed in a wider variety of manufacturing operations requiring instant solutions.
  • Dramatically reduce the time required to onboard new models. This will allow training and inference to be done faster and allow large models to be deployed much more quickly. The quicker an AI model can be deployed in production; the quicker the time-to-value and the return-on-investment (ROI).
  • Accelerate deployment of new inspections by reducing the labeling effort and iterations needed to produce a production-ready model via data summarization. Selecting small data sets for annotation means manually examining thousands of images, this is a time-consuming process that will result in - labeling of redundant data. Using ML-based automation for data summarization will accelerate the process and produce better model performance.
  • Enable Day-2 AI operations to help with data lifecycle automation and governance, model creation, reduce production errors, and provide detection of out-of-distribution data to help determine if a model’s inference is accurate. IBM believes this will allow models to be created faster without data scientists.

Maximo Application Suite

IBM’s Maximo Application Suite plays an important part in implementing large manufacturers' current and future IBM edge solutions. Maximo is an integrated public or private cloud platform that uses AI, IoT, and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs. IBM is working with several large manufacturing clients currently using Maximo to develop edge use cases, and even uses it within its own Manufacturing.

IBM has research underway to develop a more efficient method of handling life cycle management of large models that require immense amounts of data. Day 2 AI operations tasks can sometimes be more complex than initial model training, deployment, and scaling. Retraining at the edge is difficult because resources are typically limited.

Once a model is trained and deployed, it is important to monitor it for drift caused by changes in data distributions or anything that might cause a model to deviate from original requirements. Inaccuracies can adversely affect model ROI.

Day-2 AI Operations (retraining and scaling)

Day-2 AI operations consist of continual updates to AI models and applications to keep up with changes in data distributions, changes in the environment, a drop in model performance, availability of new data, and/or new regulations.

IBM recognizes the advantages of performing Day-2 AI Operations, which includes scaling and retraining at the edge. It appears that IBM is the only company with an architecture equipped to effectively handle Day-2 AI operations. That is a significant competitive advantage for IBM.

A company using an architecture that requires data to be moved from the edge back into the cloud for Day-2 related work will be unable to support many factory AI/ML applications because of the sheer number of AI/ML models to support (100s to 1000s).

“There is a huge proliferation of data at the edge that exists in multiple spokes,” Dr. Fuller said. "However, all that data isn’t needed to retrain a model. It is possible to cluster data into groups and then use sampling techniques to retrain the model. There is much value in federated learning from our point of view.”

Federated learning is a promising training solution being researched by IBM and others. It preserves privacy by using a collaboration of edge devices to train models without sharing the data with other entities. It is a good framework to use when resources are limited.

Dealing with limited resources at the edge is a challenge. IBM’s edge architecture accommodates the need to ensure resource budgets for AI applications are met, especially when deploying multiple applications and multiple models across edge locations. For that reason, IBM developed a method to deploy data and AI applications to scale Day-2 AI operations utilizing hub and spokes.

The graphic above shows the current status quo methods of performing Day-2 operations using centralized applications and a centralized data plane compared to the more efficient managed hub and spoke method with distributed applications and a distributed data plane. The hub allows it all to be managed from a single pane of glass.

Data Fabric Extensions to Hub and Spokes

IBM uses hub and spoke as a model to extend its data fabric. The model should not be thought of in the context of a traditional hub and spoke. IBM’s hub provides centralized capabilities to manage clusters and create multiples hubs that can be aggregated to a higher level. This architecture has four important data management capabilities.

  1. First, models running in unattended environments must be monitored. From an operational standpoint, detecting when a model’s effectiveness has significantly degraded and if corrective action is needed is critical.
  2. Secondly, in a hub and spoke model, data is being generated and collected in many locations creating a need for data life cycle management. Working with large enterprise clients, IBM is building unique capabilities to manage the data plane across the hub and spoke estate - optimized to meet data lifecycle, regulatory & compliance as well as local resource requirements. Automation determines which input data should be selected and labeled for retraining purposes and used to further Strengthen the model. Identification is also made for atypical data that is judged worthy of human attention.
  3. The third issue relates to AI pipeline compression and adaptation. As mentioned earlier, edge resources are limited and highly heterogeneous. While a cloud-based model might have a few hundred million parameters or more, edge models can’t afford such resource extravagance because of resource limitations. To reduce the edge compute footprint, model compression can reduce the number of parameters. As an example, it could be reduced from several hundred million to a few million.
  4. Lastly, suppose a scenario exists where data is produced at multiple spokes but cannot leave those spokes for compliance reasons. In that case, IBM Federated Learning allows learning across heterogeneous data in multiple spokes. Users can discover, curate, categorize and share data assets, data sets, analytical models, and their relationships with other organization members.

In addition to AI deployments, the hub and spoke architecture and the previously mentioned capabilities can be employed more generally to tackle challenges faced by many enterprises in consistently managing an abundance of devices within and across their enterprise locations. Management of the software delivery lifecycle or addressing security vulnerabilities across a vast estate are a case in point.

Multicloud and Edge platform

In the context of its strategy, IBM sees edge and distributed cloud as an extension of its hybrid cloud platform built around Red Hat OpenShift. One of the newer and more useful options created by the Red Hat development team is the Single Node OpenShift (SNO), a compact version of OpenShift that fits on a single server. It is suitable for addressing locations that are still servers but come in a single node, not clustered, deployment type.

For smaller footprints such as industrial PCs or computer vision boards (for example NVidia Jetson Xavier), Red Hat is working on a project which builds an even smaller version of OpenShift, called MicroShift, that provides full application deployment and Kubernetes management capabilities. It is packaged so that it can be used for edge device type deployments.

Overall, IBM and Red Hat have developed a full complement of options to address a large spectrum of deployments across different edge locations and footprints, ranging from containers to management of full-blown Kubernetes applications from MicroShift to OpenShift and IBM Edge Application Manager.

Much is still in the research stage. IBM's objective is to achieve greater consistency in terms of how locations and application lifecycle is managed.

First, Red Hat plans to introduce hierarchical layers of management with Red Hat Advanced Cluster Management (RHACM), to scale by two to three orders of magnitude the number of edge locations managed by this product. Additionally, securing edge locations is a major focus. Red Hat is continuously expanding platform security features, for example by recently including Integrity Measurement Architecture in Red Hat Enterprise Linux, or by adding Integrity Shield to protect policies in Red Hat Advanced Cluster Management (RHACM).

Red Hat is partnering with IBM Research to advance technologies that will permit it to protect platform integrity and the integrity of client workloads through the entire software supply chains. In addition, IBM Research is working with Red Hat on analytic capabilities to identify and remediate vulnerabilities and other security risks in code and configurations.

Telco network intelligence and slice management with AL/ML

Communication service providers (CSPs) such as telcos are key enablers of 5G at the edge. 5G benefits for these providers include:

  • Reduced operating costs
  • Improved efficiency
  • Increased distribution and density
  • Lower latency

The end-to-end 5G network comprises the Radio Access Network (RAN), transport, and core domains. Network slicing in 5G is an architecture that enables multiple virtual and independent end-to-end logical networks with different characteristics such as low latency or high bandwidth, to be supported on the same physical network. This is implemented using cloud-native technology enablers such as software defined networking (SDN), virtualization, and multi-access edge computing. Slicing offers necessary flexibility by allowing the creation of specific applications, unique services, and defined user groups or networks.

An important aspect of enabling AI at the edge requires IBM to provide CSPs with the capability to deploy and manage applications across various enterprise locations, possibly spanning multiple end-to-end network slices, using a single pane of glass.

5G network slicing and slice management

Network slices are an essential part of IBM's edge infrastructure that must be automated, orchestrated and optimized according to 5G standards. IBM’s strategy is to leverage AI/ML to efficiently manage, scale, and optimize the slice quality of service, measured in terms of bandwidth, latency, or other metrics.

5G and AI/ML at the edge also represent a significant opportunity for CSPs to move beyond traditional cellular services and capture new sources of revenue with new services.

Communications service providers need management and control of 5G network slicing enabled with AI-powered automation.

Dr. Fuller sees a variety of opportunities in this area. "When it comes to applying AI and ML on the network, you can detect things like intrusion detection and malicious actors," he said. "You can also determine the best way to route traffic to an end user. Automating 5G functions that run on the network using IBM network automation software also serves as an entry point.”

In IBM’s current telecom trial, IBM Research is spearheading the development of a range of capabilities targeted for the IBM Cloud Pak for Network Automation product using AI and automation to orchestrate, operate and optimize multivendor network functions and services that include:

  • End-to-end 5G network slice management with planning & design, automation & orchestration, and operations & assurance
  • Network Data and AI Function (NWDAF) that collects data for slice monitoring from 5G Core network functions, performs network analytics, and provides insights to authorized data consumers.
  • Improved operational efficiency and reduced cost

Future leverage of these capabilities by existing IBM Clients that use the Cloud Pak for Network Automation (e.g., DISH) can offer further differentiation for CSPs.

5G radio access

Open radio access networks (O-RANs) are expected to significantly impact telco 5G wireless edge applications by allowing a greater variety of units to access the system. The O-RAN concept separates the DU (Distributed Units) and CU (Centralized Unit) from a Baseband Unit in 4G and connects them with open interfaces.

O-RAN system is more flexible. It uses AI to establish connections made via open interfaces that optimize the category of a device by analyzing information about its prior use. Like other edge models, the O-RAN architecture provides an opportunity for continuous monitoring, verification, analysis, and optimization of AI models.

The IBM-telco collaboration is expected to advance O-RAN interfaces and workflows. Areas currently under development are:

  • Multi-modal (RF level + network-level) analytics (AI/ML) for wireless communication with high-speed ingest of 5G data
  • Capability to learn patterns of metric and log data across CUs and DUs in RF analytics
  • Utilization of the antenna control plane to optimize throughput
  • Primitives for forecasting, anomaly detection and root cause analysis using ML
  • Opportunity of value-added functions for O-RAN

IBM Cloud and Infrastructure

The cornerstone for the delivery of IBM's edge solutions as a service is IBM Cloud Satellite. It presents a consistent cloud-ready, cloud-native operational view with OpenShift and IBM Cloud PaaS services at the edge. In addition, IBM integrated hardware and software Edge systems will provide RHACM - based management of the platform when clients or third parties have existing managed as a service models. It is essential to note that in either case this is done within a single control plane for hubs and spokes that helps optimize execution and management from any cloud to the edge in the hub and spoke model.

IBM's focus on “edge in” means it can provide the infrastructure through things like the example shown above for software defined storage for federated namespace data lake that surrounds other hyperscaler clouds. Additionally, IBM is exploring integrated full stack edge storage appliances based on hyperconverged infrastructure (HCI), such as the Spectrum Fusion HCI, for enterprise edge deployments.

As mentioned earlier, data gravity is one of the main driving factors of edge deployments. IBM has designed its infrastructure to meet those data gravity requirements, not just for the existing hub and spoke topology but also for a future spoke-to-spoke topology where peer-to-peer data sharing becomes imperative (as illustrated with the wealth of examples provided in this article).

Wrap up

Edge is a distributed computing model. One of its main advantages is that computing, and data storage and processing is close to where data is created. Without the need to move data to the cloud for processing, real-time application of analytics and AI capabilities provides immediate solutions and drives business value.

IBM’s goal is not to move the entirety of its cloud infrastructure to the edge. That has little value and would simply function as a hub to spoke model operating on actions and configurations dictated by the hub.

IBM’s architecture will provide the edge with autonomy to determine where data should reside and from where the control plane should be exercised.

Equally important, IBM foresees this architecture evolving into a decentralized model capable of edge-to-edge interactions. IBM has no firm designs for this as yet. However, the plan is to make the edge infrastructure and platform a first-class citizen instead of relying on the cloud to drive what happens at the edge.

Developing a complete and comprehensive AI/ML edge architecture - and in fact, an entire ecosystem - is a massive undertaking. IBM faces many known and unknown challenges that must be solved before it can achieve success.

However, IBM is one of the few companies with the necessary partners and the technical and financial resources to undertake and successfully implement a project of this magnitude and complexity.

It is reassuring that IBM has a plan and that its plan is sound.

Paul Smith-Goodson is Vice President and Principal Analyst for quantum computing, artificial intelligence and space at Moor Insights and Strategy. You can follow him on Twitter for more current information on quantum, AI, and space.

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movandi.

Mon, 08 Aug 2022 03:51:00 -0500 Paul Smith-Goodson en text/html https://www.forbes.com/sites/moorinsights/2022/08/08/ibm-research-rolls-out-a-comprehensive-ai-and-ml-edge-research-strategy-anchored-by-enterprise-partnerships-and-use-cases/
Killexams : Utility Asset Management Market Industry Analysis, Opportunities, Segmentation & Forecast 2020 To 2027

The MarketWatch News Department was not involved in the creation of this content.

Utility Asset Management Market 2020 Will Provide You With Analysis Of Impact Of Latest Market Disruptions Such As Russia-Ukraine War And Covid-19 On The Market. Report Includes In-Depth Segmentation And Market Size Data By Categories, Product Types, Applications, And Geographies. Report Also Includes Comprehensive Analysis, Trends And Drivers, Restraints And Challenges, Competitive Landscape Etc.

The global utility asset management market size stood atUSD 3.31 billionin 2020 and is anticipated to attainUSD 6.20 billionby 2027, exhibiting aCAGR of 8.5%during the forecast period.

Major Utility Asset Management Market Manufacturers Covered In The Market Report Include:

  • GE
  • ABB
  • Eaton
  • Siemens
  • DNV GL
  • Aclara Technologies
  • IBM
  • Sentient Energy
  • Black and Veatch
  • Schneider Electric
  • IFS
  • Getac
  • Lindsey Manufacturing Company
  • Fujitsu

Get demo Pdf Report:https://www.fortunebusinessinsights.com/enquiry/request-sample-pdf/utility-asset-management-market-101647

Drivers and Restraints-

Increasing Number of Residential and Commercial Infrastructures to Aid Growth

The rising consumption of energy backed by the increasing number of commercial and residential infrastructures worldwide is set to augment the utility asset management market growth in the coming years. Apart from that, there has been a rapid surge in the deployment of various novel power generation techniques that are capable of fulfilling the growing demand for energy. However, unavailability of skilled workers with the correct technical knowledge for installation of complicated hardware and equipment may lower the demand for utility asset management.

Regional Analysis-

Rising Utility Expenditure to Bolster Growth in North America

Geographically, North America generated USD 1.09 billion in terms of revenue in 2020. It is set to retain its dominant position in the coming years on account of the presence of favorable regulatory policies in the region. At the same time, the rising utility expenditure, positive green energy outlook, and presence of multiple reputed utility asset management companies in the region would favor growth. Europe, on the other hand, is set to showcase substantial growth in the near future stoked by the increasing financial support from regulatory bodies to reduce emissions.

Competitive Landscape:

Key Players Focus on Partnership Strategy to Develop Utility Asset Management Solutions

The market for utility asset management is highly fragmented with the presence of numerous renowned companies. Most of them are adopting the strategy of partnerships and collaborations to co-develop unique utility asset management solutions. Some of the others are trying to enhance their product offerings by purchasing domestic companies.

Inquire Before Buying @https://www.fortunebusinessinsights.com/enquiry/queries/utility-asset-management-market-101647

Key Questions Answered In The Report:

  • What Will The Market Growth Rate Of Utility Asset Management Market In 2027?
  • What Are The Key Factors Driving The Global Market?
  • Who Are The Key Manufacturers In Space?
  • What Are The Market Opportunities, Market Risk And Market Overview Of The Global Market?
  • What Are Sales, Revenue, And Price Analysis Of Top Manufacturers Of Global Market?

Primary Objectives OfUtility Asset Management Market Report:

  • To Analyze Target Consumers And Their Preferences.
  • To Determine Potential Opportunities, Challenges, Obstacles, And Threats In TheUtility Asset Management Market Report Sales
  • To Identify And Make Suitable Business Plans According To Industry And Economic Shifts.
  • To Analyze Market Rivalry And Obtain Maximum Competitive Advantages.
  • To Mitigate Risks And Hurdles To Drive Informed Business Decisions.
  • In This Study, The Years Are Taken Into Consideration To Approximate The Market

Highlights Of The Report:

  • Market Penetration: Comprehensive Information On The Product Portfolios Of The Top Players In The Market.
  • Product Development/Innovation: Detailed Insights On The Upcoming Technologies, Randd Activities, And Product Launches In The Market
  • Competitive Assessment: In-Depth Assessment Of The Market Strategies, Geographic And Business Segments Of The Leading Players In The Market
  • Market Development: Comprehensive Information About Emerging Markets. This Report Analyzes The Market For Various Segments Across Geographies
  • Market Diversification: Exhaustive Information About New Products, Untapped Geographies, latest Developments, And Investments In The Utility Asset Management Market.

Table Of Content:

1 Market Overview

1.1 Utility Asset Management Market Introduction

1.2 Market Analysis By Type

1.3 Market Analysis By Applications

1.4 Market Analysis By Regions

1.4.1 North America (United States, Canada And Mexico)

1.4.1.1 United States Market States And Outlook (2020-2027)

1.4.1.2 Canada Market States And Outlook (2020-2027)

1.4.1.3 Mexico Market States And Outlook (2020-2027)

1.4.2 Europe (Germany, France, Uk, Russia And Italy)

1.4.2.1 Germany Market States And Outlook (2020-2027)

1.4.2.2 France Market States And Outlook (2020-2027)

1.4.2.3 Uk Market States And Outlook (2020-2027)

1.4.2.4 Russia Market States And Outlook (2020-2027)

1.4.2.5 Italy Market States And Outlook (2020-2027)

1.4.3 Asia-Pacific (China, Japan, Korea, India And Southeast Asia)

1.4.3.1 China Market States And Outlook (2020-2027)

1.4.3.2 Japan Market States And Outlook (2020-2027)

1.4.3.3 Korea Market States And Outlook (2020-2027)

1.4.3.4 India Market States And Outlook (2020-2027)

1.4.3.5 Southeast Asia Market States And Outlook (2020-2027)

1.4.4 South America, Middle East And Africa

1.4.4.1 Brazil Market States And Outlook (2020-2027)

1.4.4.2 Egypt Market States And Outlook (2020-2027)

1.4.4.3 Saudi Arabia Market States And Outlook (2020-2027)

1.4.4.4 South Africa Market States And Outlook (2020-2027)

1.4.4.5 Turkey Market States And Outlook (2020-2027)

1.5 Market Dynamics

1.5.1 Market Opportunities

1.5.2 Market Risk

1.5.3 Market Driving Force

2 Manufacturers Profiles

Continued…

Request For Customization -https://www.fortunebusinessinsights.com/enquiry/customization/utility-asset-management-market-101647

About Us:

Fortune Business Insights™ Delivers Accurate Data And Innovative Corporate Analysis, Helping Organizations Of All Sizes Make Appropriate Decisions. We Tailor Novel Solutions For Our Clients, Assisting Them To Address Various Challenges Distinct To Their Businesses. Our Aim Is To Empower Them With Holistic Market Intelligence, Providing A Granular Overview Of The Market They Are Operating In.

Contact Us:

Fortune Business Insights™ Pvt. Ltd.

Us: +1 424 253 0390

Uk: +44 2071 939123

Apac: +91 744 740 1245

Email:Sales@Fortunebusinessinsights.Com

Press Release Distributed by The Express Wire

To view the original version on The Express Wire visit Utility Asset Management Market Industry Analysis, Opportunities, Segmentation & Forecast 2020 To 2027

COMTEX_411817532/2598/2022-08-08T02:07:39

Is there a problem with this press release? Contact the source provider Comtex at editorial@comtex.com. You can also contact MarketWatch Customer Service via our Customer Center.

The MarketWatch News Department was not involved in the creation of this content.

Sun, 07 Aug 2022 18:07:00 -0500 en-US text/html https://www.marketwatch.com/press-release/utility-asset-management-market-industry-analysis-opportunities-segmentation-forecast-2020-to-2027-2022-08-08
Killexams : Advanced Report on Digital Process Automation Market by Growth, Demand, Opportunities & Forecast To 2028| IBM, Pegasystems, Appian, Oracle

Medical care, broadcast communications, IT, media, amusement, planned operations, transport and retail, are a portion of the business maturing requests for process automation. The requirement for digital process automation will be flooding during the conjecture time frame. Saving a lot of business is the expense conceivable with digital process automation. The reconciliation of cutting edge innovations is supposed to be a typical practice in many organizations. This large number of elements will massively build the digital process automation market esteem. The pointedly flooding interest for automation in ventures is an essential driver. Digital process alters the organisaions work. The smoothing out of work process is effective through demonstrates automation. The arrangement of this framework is engaging such a large number of associations. More developments and arrangements are conceivable through this framework. The low code idea of process automation consolidates business and IT. Through this, the organizations can answer their clients well. The conventional hierarchical processes are profoundly tied consuming. They are wasteful and lead to a lot of dangers in any association. The business finds it hard to adapt to clients necessities with customary techniques. In any case, with the digital process automation the business is moving toward what’s to come. Influencing, efficiency and cost administration is excellent through this.

The mix of AI and AI will bring an extensive variety of chances for the digital process automation market. Because of the disadvantages of the current innovations, businesses are prepared to pick cutting edge innovations. Both the little, medium and enormous scope association are adjusting to digital process automation for more effectiveness. Digital process automation is a wide market with both programming and administrations. A lot of hierarchical arrangements are accessible through the administration’s foundation of the market. With incorporated help associations can perform better. The advancement in the dutiable process automation will set out additional open doors and changed administrations for business. The mechanical process and AI mix is a pivotal improvement of this market. Computer based intelligence has an upper hand in any association. Forestalling human mistake, wastage and manual work is conceivable. The digital labor force can deal with any hierarchical errand effectively.

Request demo Copy of this Report: 

https://www.infinitybusinessinsights.com/request_sample.php?id=655960

The precision of the errands is more with AI digital demonstrates automation. With this advancement the end clients for the digital process automation market will develop. Likewise, request rate will be surpassing AI mix. This large number of learning experiences will prompt more extension and high consistency for the market. Absence of specialized skill is a significant limitation of the digital process automation market. The new age advancements are intricate to deal with. The innovations like modern web and progressed investigation need master support. The process automation is extreme with various kinds of automation. Specialized help is fundamental for completing the assignments proficiently. Likewise, a specialist with investigation abilities is expected to work the automation advances. The absence of accessible specialists to deal with these processes is a limitation for the market. More business information and preparation is required for the people. Without appropriate preparation or specialists the interest rate for the market can dial back. Less mindfulness can hamper the development for digital process automation.

The digital process automation market is divided based on assistance, business capability, association size, arrangement type and industry vertical.

Based on assistance, the digital process automation market is divided into arrangements and administrations.

Based on business capability, the digital process automation market is sectioned into deals process automation, production network automation claims automation and marketing automation.

Based on association size, the digital process automation market is portioned into little and medium-sized ventures (SMEs) and huge undertakings.

Based on arrangement type, the digital process automation market is divided into on-premises and cloud.

Based on industry upward, the digital process automation market is sectioned into assembling, retail and customer products, BFSI, telecom and IT, transport and planned operations, energy and utility, media and diversion, medical care, and others.

The vital territorial players of the digital process automation market are Asia pacific, Europe and North America. Prior reception of digital process automation will provoke more interest in the Asia pacific locale. The progressions in the digital process automation market are high in the estimated period. North America is the following biggest area with high development. The presence of central members will get greater advancement in North America. WE and Canada are the vital donors for high market income. The ventures from these central participants are high for the market. Likewise, Europe is seeing more interest in gauge period. There are a lot of organizations in this locale automation. This multitude of variables will contribute to high development among local players.

The vital participants of the digital process automation market are:

Nikon, Panasonic Corporation, Apex frameworks, Olympus Corporation, Amcrest innovations, LLC, Sony coporation, Zosi innovation, Robert Bosch, Cannon, Apex frameworks.

Highlights of the Digital Process Automation market report are:
– A comprehensive evaluation of all opportunities and risks in the market.
– Digital Process Automation market current developments and significant occasions.
– A deep study of business techniques for the development of the market-driving players.
– Conclusive study about the improvement plot of the market for approaching years.
– Top to bottom approach of market-express drivers, targets, and major littler scale markets.

If you need anything more than these then let us know and we will prepare the report according to your requirement.

For More Details On this Report @:

https://www.infinitybusinessinsights.com/enquiry_before_buying.php?id=655960

Table of Contents:
1. Digital Process Automation Market Overview
2. Impact on Digital Process Automation Market Industry
3. Digital Process Automation Market Competition
4. Digital Process Automation Market Production, Revenue by Region
5. Digital Process Automation Market Supply, Consumption, Export and Import by Region
6. Digital Process Automation Market Production, Revenue, Price Trend by Type
7. Digital Process Automation Market Analysis by Application
8. Digital Process Automation Market Manufacturing Cost Analysis
9. Internal Chain, Sourcing Strategy and Downstream Buyers
10. Marketing Strategy Analysis, Distributors/Traders
11. Market Effect Factors Analysis
12. Digital Process Automation Market Forecast (2022-2028)
13. Appendix

Contact Us:
473 Mundet Place, Hillside, New Jersey, United States, Zip 07205
International – +1 518 300 3575
Email: [email protected]
Website: https://www.infinitybusinessinsights.com

Thu, 04 Aug 2022 23:33:00 -0500 Newsmantraa en-US text/html https://www.digitaljournal.com/pr/advanced-report-on-digital-process-automation-market-by-growth-demand-opportunities-forecast-to-2028-ibm-pegasystems-appian-oracle
Killexams : IBM Annual Cost of Data Breach Report 2022: Record Costs Usually Passed On to Consumers, “Long Breach” Expenses Make Up Half of Total Damage

IBM’s annual Cost of Data Breach Report for 2022 is packed with revelations, and as usual none of them are good news. Headlining the report is the record-setting cost of data breaches, with the global average now at $4.35 million. The report also reveals that much of that expense comes with the data breach version of “long Covid,” expenses that are realized more than a year after the attack.

Most organizations (60%) are passing these added costs on to consumers in the form of higher prices. And while 83% of organizations now report experiencing at least one data breach, only a small minority are adopting zero trust strategies.

Security AI and automation greatly reduces expected damage

The IBM report draws on input from 550 global organizations surveyed about the period between March 2021 and March 2022, in partnership with the Ponemon Institute.

Though the average cost of a data breach is up, it is only by about 2.6%; the average in 2021 was $4.24 million. This represents a total climb of 13% since 2020, however, reflecting the general spike in cyber crime seen during the pandemic years.

Organizations are also increasingly not opting to absorb the cost of data breaches, with the majority (60%) compensating by raising consumer prices separate from any other latest increases due to inflation or supply chain issues. The report indicates that this may be an underreported upward influence on prices of consumer goods, as 83% of organizations now say that they have been breached at least once.

Brad Hong, Customer Success Manager for Horizon3.ai, sees a potential consumer backlash on the horizon once public awareness of this practice grows: “It’s already a breach of confidence to lose the confidential data of customers, and sure there’s bound to be an organization across those surveyed who genuinely did put in the effort to protect against and curb attacks, but for those who did nothing, those who, instead of creating a disaster recovery plan, just bought cyber insurance to cover the org’s operational losses, and those who simply didn’t care enough to heed the warnings, it’s the coup de grâce to then pass the cost of breaches to the same customers who are now the victims of a data breach. I’d be curious to know what percent of the 60% of organizations who increased the price of their products and services are using the extra revenue for a war chest or to actually reinforce their security—realistically, it’s most likely just being used to fill a gap in lost revenue for shareholders’ sake post-breach. Without government regulations outlining restrictions on passing cost of breach to consumer, at the least, not without the honest & measurable efforts of a corporation as their custodian, what accountability do we all have against that one executive who didn’t want to change his/her password?”

Breach costs also have an increasingly long tail, as nearly half now come over a year after the date of the attack. The largest of these are generally fines that are levied after an investigation, and decisions or settlements in class action lawsuits. While the popular new “double extortion” approach of ransomware attacks can drive long-term costs in this way, the study finds that companies paying ransom demands to settle the problem quickly aren’t necessarily seeing a large amount of overall savings: their average breach cost drops by just $610,000.

Sanjay Raja, VP of Product with Gurucul, expands on how knock-on data breach damage can continue for years: “The follow-up attack effect, as described, is a significant problem as the playbooks and solutions provided to security operations teams are overly broad and lack the necessary context and response actions for proper remediation. For example, shutting down a user or application or adding a firewall block rule or quarantining a network segment to negate an attack is not a sustainable remediation step to protect an organization on an ongoing basis. It starts with a proper threat detection, investigation and response solution. Current SIEMs and XDR solutions lack the variety of data, telemetry and combined analytics to not only identify an attack campaign and even detect variants on previously successful attacks, but also provide the necessary context, accuracy and validation of the attack to build both a precise and complete response that can be trusted. This is an even greater challenge when current solutions cannot handle complex hybrid multi-cloud architectures leading to significant blind spots and false positives at the very start of the security analyst journey.”

Rising cost of data breach not necessarily prompting dramatic security action

In spite of over four out of five organizations now having experienced some sort of data breach, only slightly over 20% of critical infrastructure companies have moved to zero trust strategies to secure their networks. Cloud security is also lagging as well, with a little under half (43%) of all respondents saying that their security practices in this area are either “early stage” or do not yet exist.

Those that have onboarded security automation and AI elements are the only group seeing massive savings: their average cost of data breach is $3.05 million lower. This particular study does not track average ransom demands, but refers to Sophos research that puts the most latest number at $812,000 globally.

The study also notes serious problems with incident response plans, especially troubling in an environment in which the average ransomware attack is now carried out in four days or less and the “time to ransom” has dropped to a matter of hours in some cases. 37% of respondents say that they do not test their incident response plans regularly. 62% say that they are understaffed to meet their cybersecurity needs, and these organizations tend to suffer over half a million more dollars in damages when they are breached.

Of course, cost of data breaches is not distributed evenly by geography or by industry type. Some are taking much bigger hits than others, reflecting trends established in prior reports. The health care industry is now absorbing a little over $10 million in damage per breach, with the average cost of data breach rising by $1 million from 2021. And companies in the United States face greater data breach costs than their counterparts around the world, at over $8 million per incident.

Shawn Surber, VP of Solutions Architecture and Strategy with Tanium, provides some insight into the unique struggles that the health care industry faces in implementing effective cybersecurity: “Healthcare continues to suffer the greatest cost of breaches but has among the lowest spend on cybersecurity of any industry, despite being deemed ‘critical infrastructure.’ The increased vulnerability of healthcare organizations to cyber threats can be traced to outdated IT systems, the lack of robust security controls, and insufficient IT staff, while valuable medical and health data— and the need to pay ransoms quickly to maintain access to that data— make healthcare targets popular and relatively easy to breach. Unlike other industries that can migrate data and sunset old systems, limited IT and security budgets at healthcare orgs make migration difficult and potentially expensive, particularly when an older system provides a small but unique function or houses data necessary for compliance or research, but still doesn’t make the cut to transition to a newer system. Hackers know these weaknesses and exploit them. Additionally, healthcare orgs haven’t sufficiently updated their security strategies and the tools that manufacturers, IT software vendors, and the FDA have made haven’t been robust enough to thwart the more sophisticated techniques of threat actors.”

Familiar incident types also lead the list of the causes of data breaches: compromised credentials (19%), followed by phishing (16%). Breaches initiated by these methods also tended to be a little more costly, at an average of $4.91 million per incident.

Global average cost of #databreach is now $4.35M, up 13% since 2020. Much of that are realized more than a year after the attack, and 60% of organizations are passing the costs on to consumers in the form of higher prices. #cybersecurity #respectdataClick to Tweet

Cutting the cost of data breach

Though the numbers are never as neat and clean as averages would indicate, it would appear that the cost of data breaches is cut dramatically for companies that implement solid automated “deep learning” cybersecurity tools, zero trust systems and regularly tested incident response plans. Mature cloud security programs are also a substantial cost saver.

Mon, 01 Aug 2022 10:00:00 -0500 Scott Ikeda en-US text/html https://www.cpomagazine.com/cyber-security/ibm-annual-cost-of-data-breach-report-2022-record-costs-usually-passed-on-to-consumers-long-breach-expenses-make-up-half-of-total-damage/
Killexams : Zero trust: Chaos creates cybercriminal opportunities

If there is any word to best describe the first few years of the decade, it is chaotic. And chaos is where cybercriminals flourish. While many fleets and other transportation industry organizations and businesses are more secure than last decade, there are more threats to the industry, which could impact fleets, their customers, and supply chains.

In the past year, the transportation industry was among the top 10 most targeted sectors by cybercriminals, according to a 2022 IBM Security study. While transportation was the seventh-most cyberattack-targeted industry, industries relying on trucking and other transportation services, such as manufacturing (No. 1), energy (No. 4), and retail/wholesale (No. 5), were victims of ransomware and business email compromise (BEC) attacks, according to the study.

See also: Still waiting on blockchain to catch up with the hype

These attacks, particularly against manufacturing, which accounted for nearly a quarter of all cyberattacks worldwide in 2021, added to the supply chain pressures created during the COVID-19 pandemic.

"Cybercriminals usually chase the money. Now with ransomware, they are chasing leverage," said Charles Henderson, head of IBM X-Force. "Businesses should recognize that vulnerabilities are holding them in a deadlock—as ransomware actors use that to their advantage. This is a non-binary challenge. The attack surface is only growing larger, so instead of operating under the assumption that every vulnerability in their environment has been patched, businesses should operate under an assumption of compromise and enhance their vulnerability management with a zero trust strategy."

Joe Russo, VP of IT and Security at Isaac Instruments, a trucking technology company, said more companies are shifting toward “zero-trust.” It’s a new security approach that assumes a breach has already happened—so it increases the difficulty for an attacker to move through a company’s network.

“Zero trust is something that can help all fleets,” Russo told FleetOwner. Fundamentally, zero trust is understanding where critical data resides and who has access to it. It’s one of the bases for blockchain. Then, he explained, fleets should create robust verification measures throughout a network to ensure only the right people are accessing that crucial data in the right way.

Transportation industry security improves

IBM’s study found that 4% of all attacks were aimed at the transportation industry, which made it the seventh-most targeted group in 2021. Transportation was No. 9 in 2020. IBM found that as international borders and transportation networks reopened in 2021, it renewed cybercriminal interest in transportation. While transportation ranked lower overall in 2020, it saw more cyberattacks. 

The transportation industry had already started taking cyber issues more seriously last year, according to Ben Barnes, chief information security officer and VP of IT services for transportation solutions provider McLeod Software

See also: How to reduce the risk of a data breach

“I think we, as an industry, have come a long way in our cybersecurity,” he told FleetOwner. “A lack of cyber adoption was our big hurdle for a long time. I don’t think we suffer that anymore.”

While the transportation industry was once the “low-hanging fruit” for cybercriminals, that is no longer the case, Barnes said. “I think a lot of the attacks in the transportation industry now are very targeted. It’s a high-value market now,” he explained. “High value doesn’t mean profitable, but there’s a lot of revenue; there’s a lot of dollars in transportation that are moving. And that makes us very likable for a thief.”

Malicious insiders—those who intentionally abuse legitimate credentials to steal information—was the top attack type against transportation organizations in 2021, according to the IBM study. These attacks made up 29% of those in the industry. Ransomware, remote access trojans (RATs), data theft, credential harvesting, and server access were also aimed at transportation organizations.

Half of the incidents IBM X-Force remediated at transportation companies originated with phishing emails, followed by stolen credentials (33%), and vulnerability exploitation (17%).

Russo noted that during the pandemic, as more companies were dealing with remote workers and more entry points for attacks, cybersecurity technologies improved. “If there’s a ransomware attack, it can be isolated to just that device so it doesn’t spread,” he explained. “A lot more proactive and containment is happening than in the past.”

Transportation targets

While transportation is no longer one of the top five targets for cybercriminals, it’s no reason for fleets and similar businesses to rest, Russo said. 

“With the Russian war in Ukraine, hackers are going after high-value targets, such as financial systems and health care,” Russo explained. “They haven’t gone down the list yet and hit transportation. But everyone must be vigilant—it could hit anytime.” 

See also: Are cybercriminals waiting for an opportune time to attack U.S. trucks?

When the fragility of U.S. supply chains was exposed during the COVID pandemic, cybercriminals were also shown how attacks could affect specific transportation organizations and businesses such as fleets, according to John Sheehy, SVP of research and strategy for IOActive

“You might be attacked because of who your client is—or who their client is,” Sheehy told FleetOwner. He explained that a criminal looking to infiltrate a high-value target could use a fleet’s weaker cybersecurity as a way to get into a fleet customer’s network. That’s why he believes sharing information about company security breaches can contribute to the common good.

“Empowering them with the information they need to make decisions to protect themselves and their clients is very helpful,” Sheehy said.

Cyberattacks aren’t going away, McLeod’s Barnes said. And like all business practices, companies need to review and revisit their cybersecurity practices regularly. 

“We’re all targets because we’re all part of the transportation sector—but there is strength in collective action,” he said. The transportation industry needs to work together to combat cybercrime. As more companies take steps to protect their IT systems, the transportation sector will become a less attractive target for cybercriminals. If we can raise awareness and take action to defeat cybercrime, the entire industry will benefit.”

Fri, 29 Jul 2022 01:19:00 -0500 text/html https://www.fleetowner.com/technology/article/21246668/chaos-creates-cybercriminal-opportunities
Killexams : Identity and Access Management-as-a-service (IDaaS) Market 2022: Comprehensive Study by Top Key Players Broadcom, IBM, Microsoft

New Jersey, N.J., July 27, 2022 The Identity and Access Management-as-a-service (IDaaS) Market research report provides all the information related to the industry. It gives the outlook of the market by giving authentic data to its client which helps to make essential decisions. It gives an overview of the market which includes its definition, applications and developments, and manufacturing technology. This Identity and Access Management-as-a-service (IDaaS) market research report tracks all the latest developments and innovations in the market. It gives the data regarding the obstacles while establishing the business and guides to overcome the upcoming challenges and obstacles.

Identity as a service or IDaaS is an application delivery model (similar to software as a service or SaaS) that enables users to connect to and use the cloud of identity management services. More and more business organizations, including governing bodies, banks, financial institutions, and retail companies, are adopting digital business models. This triggered the need to increase the potential for reducing identity and access management system fraud and identity authentication methods and, ultimately, the growth of the IDaaS market.

Get the PDF demo Copy (Including FULL TOC, Graphs, and Tables) of this report @:

https://www.a2zmarketresearch.com/sample-request/658020

Competitive landscape:

This Identity and Access Management-as-a-service (IDaaS) research report throws light on the major market players thriving in the market; it tracks their business strategies, financial status, and upcoming products.

Some of the Top companies Influencing this Market include:Broadcom, IBM, Microsoft, Ping Identity, Salesforce.com,

Market Scenario:

Firstly, this Identity and Access Management-as-a-service (IDaaS) research report introduces the market by providing an overview which includes definition, applications, product launches, developments, challenges, and regions. The market is forecasted to reveal strong development by driven consumption in various markets. An analysis of the current market designs and other basic characteristics is provided in the Identity and Access Management-as-a-service (IDaaS) report.

Regional Coverage:

The region-wise coverage of the market is mentioned in the report, mainly focusing on the regions:

  • North America
  • South America
  • Asia and Pacific region
  • Middle East and Africa
  • Europe

Segmentation Analysis of the market

The market is segmented on the basis of the type, product, end users, raw materials, etc. the segmentation helps to deliver a precise explanation of the market

Market Segmentation: By Type

Cloud
Hybrid
On-Premise

Market Segmentation: By Application

BFSI
Oil & Gas
Telecom & IT
Education
Healthcare
Public Sector & Utilities
Manufacturing
Others

For Any Query or Customization: https://a2zmarketresearch.com/ask-for-customization/658020

An assessment of the market attractiveness with regard to the competition that new players and products are likely to present to older ones has been provided in the publication. The research report also mentions the innovations, new developments, marketing strategies, branding techniques, and products of the key participants present in the global Identity and Access Management-as-a-service (IDaaS) market. To present a clear vision of the market the competitive landscape has been thoroughly analyzed utilizing the value chain analysis. The opportunities and threats present in the future for the key market players have also been emphasized in the publication.

This report aims to provide:

  • A qualitative and quantitative analysis of the current trends, dynamics, and estimations from 2022 to 2029.
  • The analysis tools such as SWOT analysis, and Porter’s five force analysis are utilized which explain the potency of the buyers and suppliers to make profit-oriented decisions and strengthen their business.
  • The in-depth analysis of the market segmentation helps to identify the prevailing market opportunities.
  • In the end, this Identity and Access Management-as-a-service (IDaaS) report helps to save you time and money by delivering unbiased information under one roof.

Table of Contents

Global Identity and Access Management-as-a-service (IDaaS) Market Research Report 2022 – 2029

Chapter 1 Identity and Access Management-as-a-service (IDaaS) Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions

Chapter 6 Global Production, Revenue (Value), Price Trend by Type

Chapter 7 Global Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Global Identity and Access Management-as-a-service (IDaaS) Market Forecast

Buy Exclusive Report @: https://www.a2zmarketresearch.com/checkout

Contact Us:

Roger Smith

1887 WHITNEY MESA DR HENDERSON, NV 89014

[email protected]

+1 775 237 4157

Wed, 27 Jul 2022 01:08:00 -0500 A2Z Market Research en-US text/html https://www.digitaljournal.com/pr/identity-and-access-management-as-a-service-idaas-market-2022-comprehensive-study-by-top-key-players-broadcom-ibm-microsoft
Killexams : CIOReview Names Cobalt Iron Among 10 Most Promising IBM Solution Providers 2022

Cobalt Iron Inc., a leading provider of SaaS-based enterprise data protection, today announced that the company has been deemed one of the 10 Most Promising IBM Solution Providers 2022 by CIOReview Magazine. The annual list of companies is selected by a panel of experts and members of CIOReview Magazine's editorial board to recognize and promote innovation and entrepreneurship. A technology partner for IBM, Cobalt Iron earned the distinction based on its Compass® enterprise SaaS backup platform for monitoring, managing, provisioning, and securing the entire enterprise backup landscape.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20220728005043/en/

Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection. (Graphic: Business Wire)

Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection. (Graphic: Business Wire)

According to CIOReview, "Cobalt Iron has built a patented cyber-resilience technology in a SaaS model to alleviate the complexities of managing large, multivendor setups, providing an effectual humanless backup experience. This SaaS-based data protection platform, called Compass, leverages strong IBM technologies. For example, IBM Spectrum Protect is embedded into the platform from a data backup and recovery perspective. ... By combining IBM's technologies and the intellectual property built by Cobalt Iron, the company delivers a secure, modernized approach to data protection, providing a 'true' software as a service."

Through proprietary technology, the Compass data protection platform integrates with, automates, and optimizes best-of-breed technologies, including IBM Spectrum Protect, IBM FlashSystem, IBM Red Hat Linux, IBM Cloud, and IBM Cloud Object Storage. Compass enhances and extends IBM technologies by automating more than 80% of backup infrastructure operations, optimizing the backup landscape through analytics, and securing backup data, making it a valuable addition to IBM's data protection offerings.

CIOReview also praised Compass for its simple and intuitive interface to display a consolidated view of data backups across an entire organization without logging in to every backup product instance to extract data. The mahine learning-enabled platform also automates backup processes and infrastructure, and it uses open APIs to connect with ticket management systems to generate tickets automatically about any backups that need immediate attention.

To ensure the security of data backups, Cobalt Iron has developed an architecture and security feature set called Cyber Shield for 24/7 threat protection, detection, and analysis that improves ransomware responsiveness. Compass is also being enhanced to use several patented techniques that are specific to analytics and ransomware. For example, analytics-based cloud brokering of data protection operations helps enterprises make secure, efficient, and cost-effective use of their cloud infrastructures. Another patented technique - dynamic IT infrastructure optimization in response to cyberthreats - offers unique ransomware analytics and automated optimization that will enable Compass to reconfigure IT infrastructure automatically when it detects cyberthreats, such as a ransomware attack, and dynamically adjust access to backup infrastructure and data to reduce exposure.

Compass is part of IBM's product portfolio through the IBM Passport Advantage program. Through Passport Advantage, IBM sellers, partners, and distributors around the world can sell Compass under IBM part numbers to any organizations, particularly complex enterprises, that greatly benefit from the automated data protection and anti-ransomware solutions Compass delivers.

CIOReview's report concludes, "With such innovations, all eyes will be on Cobalt Iron for further advancements in humanless, secure data backup solutions. Cobalt Iron currently focuses on IP protection and continuous R&D to bring about additional cybersecurity-related innovations, promising a more secure future for an enterprise's data."

About Cobalt Iron

Cobalt Iron was founded in 2013 to bring about fundamental changes in the world's approach to secure data protection, and today the company's Compass® is the world's leading SaaS-based enterprise data protection system. Through analytics and automation, Compass enables enterprises to transform and optimize legacy backup solutions into a simple cloud-based architecture with built-in cybersecurity. Processing more than 8 million jobs a month for customers in 44 countries, Compass delivers modern data protection for enterprise customers around the world. www.cobaltiron.com

Product or service names mentioned herein are the trademarks of their respective owners.

Link to Word Doc: www.wallstcom.com/CobaltIron/220728-Cobalt_Iron-CIOReview_Top_IBM_Provider_2022.docx

Photo Link: www.wallstcom.com/CobaltIron/Cobalt_Iron_CIO_Review_Top_IBM_Solution_Provider_Award_Logo.pdf

Photo Caption: Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection.

Follow Cobalt Iron

https://twitter.com/cobaltiron
https://www.linkedin.com/company/cobalt-iron/
https://www.youtube.com/user/CobaltIronLLC

[ Back To TMCnet.com's Homepage ]

Thu, 28 Jul 2022 02:51:00 -0500 text/html https://www.tmcnet.com/usubmit/2022/07/28/9646864.htm
Killexams : Global Healthcare Decision Support & IBM Watson Market Size, Share & Trends Analysis Report by Type, By Application, And Segment Forecasts to 2029

The MarketWatch News Department was not involved in the creation of this content.

Jul 29, 2022 (Heraldkeepers) -- Pune India – Global Healthcare Decision Support & IBM Watson Market Research Report 2020-2026 thinks about key breakdowns in the Industry with insights about the market drivers and market restrictions. The report illuminates accumulating an all encompassing rundown of factual investigation for the market scape. While setting up this expert and top to bottom statistical surveying report, client necessity has been kept into center. The report covers a few overwhelming elements encompassing the worldwide Healthcare Decision Support & IBM Watson market, for example, worldwide appropriation channels, makers, market size, and other logical components that include the whole scene of the market. The examination archive intends to direct perusers in experiencing the impediments that are featured after a concentrated investigation.

To Know How COVID-19 Pandemic Will Impact Healthcare Decision Support & IBM Watson Market | Get a demo Copy of Report, Click Here: https://www.reportsweb.com/inquiry&RW00014675433/sample

Key Companies profiled in this research study are:

EMC Health Care Ltd.
AT&T
Cisco
Vangent Inc.
American Well Systems
Accenture
McKesson Corporation
IBM Watson
Aetna
Optum Inc.

The report has included vital parts of the business, for example, item advancement and determination, innovation, specialty development openings. The report encompasses business bits of knowledge at the broad commercial center. It assembles a serious scene that rethinks development openings alongside an assortment of item types, applications, and a worldwide circulation channel framework. It gives a broad examination of the provincial advertising techniques, market difficulties, and driving components, deals records, net benefit, and business channel disseminations. The market study report additionally includes the top vital participants in the Global Healthcare Decision Support & IBM Watson market.

NOTE: Our analysts monitoring the situation across the globe explains that the market will generate remunerative prospects for producers post the COVID-19 crisis. The report aims to provide an additional illustration of the latest scenario, economic slowdown, and COVID-19 impact on the overall industry.

Years to be Considered in this Healthcare Decision Support & IBM Watson Market Report:

History Year: 2017-2019

Base Year: 2020

Estimated Year: 2021

Forecast Year: 2022-2028

Healthcare Decision Support & IBM Watson Regional and Country-wise Analysis:

North America (U.S., Canada, Mexico)

Europe (U.K., France, Germany, Spain, Italy, Central & Eastern Europe, CIS)

Asia Pacific (China, Japan, South Korea, ASEAN, India, Rest of Asia Pacific)

Latin America (Brazil, Rest of Latin America)

The Middle East and Africa (Turkey, GCC, Rest of the Middle East and Africa)

Rest of the World....

In Chapter 8 and Chapter 10.3, based on types, the Healthcare Decision Support & IBM Watson market from 2017 to 2029 is primarily split into:
Artificial Intelligence
Data
Analytics
Cloud Computing

In Chapter 9 and Chapter 10.4, based on applications, the Healthcare Decision Support & IBM Watson market from 2017 to 2029 covers:
IT- Healthcare Solutions
Clinical Data Management
Genomics
Drug Discovery

The purposes of this analysis are:

  1. To characterize, portray, and check the Healthcare Decision Support & IBM Watson market based on product type, application, and region.
  2. To estimate and inspect the size of the Healthcare Decision Support & IBM Watson market (in terms of value) in six key regions, specifically, North and South America, Western Europe, Central & Eastern Europe, the Middle East, Africa, and the Asia-Pacific.
  3. To estimate and inspect the Healthcare Decision Support & IBM Watson markets at country-level in every region.
  4. To strategically investigate every sub-market about personal development trends and its contribution to the Healthcare Decision Support & IBM Watson market.
  5. To look at possibilities in the Healthcare Decision Support & IBM Watson market for shareholder by recognizing excessive-growth segments of the market.

Click here to avail lucrative discounts on our latest reports. We offer student, enterprise, and special periodic discounts to our clientele. Please fill the inquiry form below to know more – https://www.reportsweb.com/inquiry&RW00014675433/discount

Our report offers:

Market share assessments for the regional and country-level segments.

Inventory network patterns planning the most latest innovative progressions.

Key suggestions for the new participants.

Piece of the pie examination of the top business players.

Market conjectures for at least 9 years of the relative multitude of referenced fragments, sub-portions, and the local business sectors.

Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and suggestions).

Organization profiling with point by point techniques, financials, and ongoing turns of events.

Serious arranging planning the key regular patterns.

Key suggestions in key business portions dependent on market assessments.

Customization of the Report: This report can be customized to meet the client's requirements. Please connect with our sales team

((sales@reportsweb.com),), who will ensure that you get a report that suits your needs.

About Us:

ReportsWeb is a one stop shop of market research reports and solutions to various companies across the globe. We help our clients in their decision support system by helping them choose most relevant and cost effective research reports and solutions from various publishers.

The market research industry has changed in last decade. As corporate focus has shifted to niche markets and emerging countries, a number of publishers have stepped in to fulfil these information needs. We have experienced and trained staff that helps you navigate different options and lets you choose best research solution at most effective cost.

Contact Us:

Sameer Joshi

Phone:+1-646-491-9876 || +91-20-67271633 Rest of the World

Email: sales@reportsweb.com

Web: www.reportsweb.com

COMTEX_411220174/2582/2022-07-29T04:23:15

Is there a problem with this press release? Contact the source provider Comtex at editorial@comtex.com. You can also contact MarketWatch Customer Service via our Customer Center.

The MarketWatch News Department was not involved in the creation of this content.

Thu, 28 Jul 2022 20:23:00 -0500 en-US text/html https://www.marketwatch.com/press-release/global-healthcare-decision-support-ibm-watson-market-size-share-trends-analysis-report-by-type-by-application-and-segment-forecasts-to-2029-2022-07-29
Killexams : CIOReview Names Cobalt Iron Among 10 Most Promising IBM Solution Providers 2022

LAWRENCE, Kan.--(BUSINESS WIRE)--Jul 28, 2022--

Cobalt Iron Inc., a leading provider of SaaS-based enterprise data protection, today announced that the company has been deemed one of the 10 Most Promising IBM Solution Providers 2022 by CIOReview Magazine. The annual list of companies is selected by a panel of experts and members of CIOReview Magazine’s editorial board to recognize and promote innovation and entrepreneurship. A technology partner for IBM, Cobalt Iron earned the distinction based on its Compass ® enterprise SaaS backup platform for monitoring, managing, provisioning, and securing the entire enterprise backup landscape.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20220728005043/en/

Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection. (Graphic: Business Wire)

According to CIOReview, “Cobalt Iron has built a patented cyber-resilience technology in a SaaS model to alleviate the complexities of managing large, multivendor setups, providing an effectual humanless backup experience. This SaaS-based data protection platform, called Compass, leverages strong IBM technologies. For example, IBM Spectrum Protect is embedded into the platform from a data backup and recovery perspective. ... By combining IBM’s technologies and the intellectual property built by Cobalt Iron, the company delivers a secure, modernized approach to data protection, providing a ‘true’ software as a service.”

Through proprietary technology, the Compass data protection platform integrates with, automates, and optimizes best-of-breed technologies, including IBM Spectrum Protect, IBM FlashSystem, IBM Red Hat Linux, IBM Cloud, and IBM Cloud Object Storage. Compass enhances and extends IBM technologies by automating more than 80% of backup infrastructure operations, optimizing the backup landscape through analytics, and securing backup data, making it a valuable addition to IBM’s data protection offerings.

CIOReview also praised Compass for its simple and intuitive interface to display a consolidated view of data backups across an entire organization without logging in to every backup product instance to extract data. The machine learning-enabled platform also automates backup processes and infrastructure, and it uses open APIs to connect with ticket management systems to generate tickets automatically about any backups that need immediate attention.

To ensure the security of data backups, Cobalt Iron has developed an architecture and security feature set called Cyber Shield for 24/7 threat protection, detection, and analysis that improves ransomware responsiveness. Compass is also being enhanced to use several patented techniques that are specific to analytics and ransomware. For example, analytics-based cloud brokering of data protection operations helps enterprises make secure, efficient, and cost-effective use of their cloud infrastructures. Another patented technique — dynamic IT infrastructure optimization in response to cyberthreats — offers unique ransomware analytics and automated optimization that will enable Compass to reconfigure IT infrastructure automatically when it detects cyberthreats, such as a ransomware attack, and dynamically adjust access to backup infrastructure and data to reduce exposure.

Compass is part of IBM’s product portfolio through the IBM Passport Advantage program. Through Passport Advantage, IBM sellers, partners, and distributors around the world can sell Compass under IBM part numbers to any organizations, particularly complex enterprises, that greatly benefit from the automated data protection and anti-ransomware solutions Compass delivers.

CIOReview’s report concludes, “With such innovations, all eyes will be on Cobalt Iron for further advancements in humanless, secure data backup solutions. Cobalt Iron currently focuses on IP protection and continuous R&D to bring about additional cybersecurity-related innovations, promising a more secure future for an enterprise’s data.”

About Cobalt Iron

Cobalt Iron was founded in 2013 to bring about fundamental changes in the world’s approach to secure data protection, and today the company’s Compass ® is the world’s leading SaaS-based enterprise data protection system. Through analytics and automation, Compass enables enterprises to transform and optimize legacy backup solutions into a simple cloud-based architecture with built-in cybersecurity. Processing more than 8 million jobs a month for customers in 44 countries, Compass delivers modern data protection for enterprise customers around the world. www.cobaltiron.com

Product or service names mentioned herein are the trademarks of their respective owners.

Link to Word Doc:www.wallstcom.com/CobaltIron/220728-Cobalt_Iron-CIOReview_Top_IBM_Provider_2022.docx

Photo Link:www.wallstcom.com/CobaltIron/Cobalt_Iron_CIO_Review_Top_IBM_Solution_Provider_Award_Logo.pdf

Photo Caption: Cobalt Iron Compass ® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection.

Follow Cobalt Iron

https://twitter.com/cobaltiron

https://www.linkedin.com/company/cobalt-iron/

https://www.youtube.com/user/CobaltIronLLC

View source version on businesswire.com:https://www.businesswire.com/news/home/20220728005043/en/

CONTACT: Agency Contact:

Sunny Branson

Wall Street Communications

Tel: +1 801 326 9946

Email:sunny@wallstcom.com

Web:www.wallstcom.comCobalt Iron Contact:

Mary Spurlock

VP of Marketing

Tel: +1 785 979 9461

Email:maspurlock@cobaltiron.com

Web:www.cobaltiron.com

KEYWORD: EUROPE UNITED STATES NORTH AMERICA KANSAS

INDUSTRY KEYWORD: DATA MANAGEMENT SECURITY TECHNOLOGY SOFTWARE NETWORKS INTERNET

SOURCE: Cobalt Iron

Copyright Business Wire 2022.

PUB: 07/28/2022 09:00 AM/DISC: 07/28/2022 09:03 AM

http://www.businesswire.com/news/home/20220728005043/en

Thu, 28 Jul 2022 01:29:00 -0500 en text/html https://www.eagletribune.com/region/cioreview-names-cobalt-iron-among-10-most-promising-ibm-solution-providers-2022/article_56f7dda7-cbd5-586a-9d5f-f882022100da.html
Killexams : CIOReview Names Cobalt Iron Among 10 Most Promising IBM Solution Providers 2022

LAWRENCE, Kan., July 28, 2022--(BUSINESS WIRE)--Cobalt Iron Inc., a leading provider of SaaS-based enterprise data protection, today announced that the company has been deemed one of the 10 Most Promising IBM Solution Providers 2022 by CIOReview Magazine. The annual list of companies is selected by a panel of experts and members of CIOReview Magazine’s editorial board to recognize and promote innovation and entrepreneurship. A technology partner for IBM, Cobalt Iron earned the distinction based on its Compass® enterprise SaaS backup platform for monitoring, managing, provisioning, and securing the entire enterprise backup landscape.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20220728005043/en/

Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection. (Graphic: Business Wire)

According to CIOReview, "Cobalt Iron has built a patented cyber-resilience technology in a SaaS model to alleviate the complexities of managing large, multivendor setups, providing an effectual humanless backup experience. This SaaS-based data protection platform, called Compass, leverages strong IBM technologies. For example, IBM Spectrum Protect is embedded into the platform from a data backup and recovery perspective. ... By combining IBM’s technologies and the intellectual property built by Cobalt Iron, the company delivers a secure, modernized approach to data protection, providing a ‘true’ software as a service."

Through proprietary technology, the Compass data protection platform integrates with, automates, and optimizes best-of-breed technologies, including IBM Spectrum Protect, IBM FlashSystem, IBM Red Hat Linux, IBM Cloud, and IBM Cloud Object Storage. Compass enhances and extends IBM technologies by automating more than 80% of backup infrastructure operations, optimizing the backup landscape through analytics, and securing backup data, making it a valuable addition to IBM’s data protection offerings.

CIOReview also praised Compass for its simple and intuitive interface to display a consolidated view of data backups across an entire organization without logging in to every backup product instance to extract data. The machine learning-enabled platform also automates backup processes and infrastructure, and it uses open APIs to connect with ticket management systems to generate tickets automatically about any backups that need immediate attention.

To ensure the security of data backups, Cobalt Iron has developed an architecture and security feature set called Cyber Shield for 24/7 threat protection, detection, and analysis that improves ransomware responsiveness. Compass is also being enhanced to use several patented techniques that are specific to analytics and ransomware. For example, analytics-based cloud brokering of data protection operations helps enterprises make secure, efficient, and cost-effective use of their cloud infrastructures. Another patented technique — dynamic IT infrastructure optimization in response to cyberthreats — offers unique ransomware analytics and automated optimization that will enable Compass to reconfigure IT infrastructure automatically when it detects cyberthreats, such as a ransomware attack, and dynamically adjust access to backup infrastructure and data to reduce exposure.

Compass is part of IBM’s product portfolio through the IBM Passport Advantage program. Through Passport Advantage, IBM sellers, partners, and distributors around the world can sell Compass under IBM part numbers to any organizations, particularly complex enterprises, that greatly benefit from the automated data protection and anti-ransomware solutions Compass delivers.

CIOReview’s report concludes, "With such innovations, all eyes will be on Cobalt Iron for further advancements in humanless, secure data backup solutions. Cobalt Iron currently focuses on IP protection and continuous R&D to bring about additional cybersecurity-related innovations, promising a more secure future for an enterprise’s data."

About Cobalt Iron

Cobalt Iron was founded in 2013 to bring about fundamental changes in the world’s approach to secure data protection, and today the company’s Compass® is the world’s leading SaaS-based enterprise data protection system. Through analytics and automation, Compass enables enterprises to transform and optimize legacy backup solutions into a simple cloud-based architecture with built-in cybersecurity. Processing more than 8 million jobs a month for customers in 44 countries, Compass delivers modern data protection for enterprise customers around the world. www.cobaltiron.com

Product or service names mentioned herein are the trademarks of their respective owners.

Link to Word Doc: www.wallstcom.com/CobaltIron/220728-Cobalt_Iron-CIOReview_Top_IBM_Provider_2022.docx

Photo Link: www.wallstcom.com/CobaltIron/Cobalt_Iron_CIO_Review_Top_IBM_Solution_Provider_Award_Logo.pdf

Photo Caption: Cobalt Iron Compass® is a SaaS-based data protection platform leveraging strong IBM technologies for delivering a secure, modernized approach to data protection.

Follow Cobalt Iron

https://twitter.com/cobaltiron
https://www.linkedin.com/company/cobalt-iron/
https://www.youtube.com/user/CobaltIronLLC

View source version on businesswire.com: https://www.businesswire.com/news/home/20220728005043/en/

Contacts

Agency Contact:
Sunny Branson
Wall Street Communications
Tel: +1 801 326 9946
Email: sunny@wallstcom.com
Web: www.wallstcom.com

Cobalt Iron Contact:
Mary Spurlock
VP of Marketing
Tel: +1 785 979 9461
Email: maspurlock@cobaltiron.com
Web: www.cobaltiron.com

Thu, 28 Jul 2022 01:06:00 -0500 en-US text/html https://finance.yahoo.com/news/cioreview-names-cobalt-iron-among-130000149.html
C9010-022 exam dump and training guide direct download
Training Exams List