Companies everywhere are embarking on bold and ambitious digital transformation journeys. To achieve success, many have chosen to rely on SAP's Enterprise Resource Planning (ERP) systems.
Designed to replace earlier generation ERP systems, SAP has launched SAP S/4HANA, which allows companies to embrace the digital reinvention era more fully.
For companies wishing to adopt SAP S/4HANA — regardless of their industry or where they stand in their implementation journey — this whitepaper provides critical insight into:
RHEL 9.0, the latest major release of Red Hat Enterprise Linux, delivers tighter security, as well as improved installation, distribution, and management for enterprise server and cloud environments.
The operating system, code named Plow, is a significant upgrade over RHEL 8.0 and makes it easier for application developers to test and deploy containers.
Available in server and desktop versoins, RHEL remains one of the top Linux distributions for running enterprise workloads because of its stability, dependability, and robustness.
It is free for software-development purposes, but instances require registration with the Red Hat Subscription Management (RHSM) service. Red Hat, owned by IBM, provides 24X7 subscription-based customer support as well as professional integration services. With the money Red Hat receives from subscriptions, it supports other open source efforts, including those that provide upstream features that eventually end up in RHEL itself.
RHEL 9 can be run on a variety of physical hardware, as a virtual machine on hypervisors, in containers, or as instances in Infrastructure as a Service (IaaS) public cloud services. It supports legacy x86 hardware as well as 64-bit x86_64-v2, aarch64, and ARMv8.0-A hardware architectures. RHEL 9 supports IBM Power 9, Power 10, and Z-series (z14) hardware platforms.
RHEL also supports a variety of data-storage file systems, including the common Ext4 file system, GFS2 and XFS. Legacy support for Ext2, Ext3, and vfat (FAT32) still exists.
RHEL scales to large amounts of persistent and transient store, and RHEL 9 increases maximum amount of memory to 48 TB for x86_64 architectures.
The first step is downloading the operating system and following some straight-forward steps.
When installing RHEL 9, users are prompeted for "Software Selection" options, and we chose Server with GUI. There are others such as Minimal Install, Server, Workstation, Custom Operating System, and Virtualization Host.
At this point, additional software can be chosen based on the environment and install functions like DNS Name Server, File and Storage Server, Debugging Tools, GNOME, and Guest Agents, if running a hypervisor. These allow tailoring the type of install based on the role of the server. Next, users can select add-ons for additional environment software to install automatically.
RHEL9 comes with Linux Kernel 5.14.0-70. The latest Linux kernel is 5.19, but Red Hat prioritizes stability and supportability over bleeding-edge features of the latest versions.
Server with GUI or any of the desktop variants of RHEL 9 come with the GNOME 40 desktop environment. (The latest GNOME version is 42.) For a graphical interface, RHEL 9 uses the Wayland 1.19 graphics-display server protocol with NVIDIA drivers. Wayland is the C library communications protocol that specifies how data will be sent to the display server and clients. The latest Wayland release is 1.21 with RHEL again opting for stability and general availability.
The RHEL 9 desktop environment, like most Linux distributions, can run the LibreOffice 7.1.8.1 set of desktop productivity applications. The latest LibreOffice version is 7.3.
RHEL is a solid operating system for application developers who plan to move working code into production. RHEL 9 comes with GNU Compiler Collection (GCC) 11.2.1 with LLVM, glibc 2.34, and binutils 2.35. Link Time Optimization (LTO) is now enabled by default to help make executables smaller and more efficient.
RHEL 9 comes with Python 3.9 installed by default and supports modern programming languages like Rust and Go. RHEL 9 also comes with updated programming languages including Node.js, Ruby 3.0.3, Perl 5.32, and PHP 8.0.
Red Hat offers the OpenShift Container Platform as its primary product for running Linux containers in a Kubernetes management environment. OpenShift runs on RHEL, and RHEL 9 has available Universal Base Image (UBI) images to support building containerized applications. RHEL 9 also has automatic container updates and rollbacks, and the Podman tool can help notify DevOps teams if containers are failing and automatically rollback to known-good configurations.
Linux software-package management systems have been evolving in exact years. The yum (Yellow-Dog Updater Modified) software update utility is being deprecated, but the command itself is still supported. The transition to dnf (Dandified Yum) has occurred, and the yum command is just a symbolic link to dnf3.
RHEL 9 comes with Red Hat Package Manager (RPM) 4.16, and the rpm command can still be used to install files with the .rpm file extension. Flatpak (formerly sdg-app) is another method of packaging and distributing software to Linux systems. Flatpak defines permissions and resource access that apps require.
RHEL 9 also supports the Red Hat Software Collections (RHSCL) for releasing semi-annual stable updates of critical application software. RHSCL provides updates to software-development tools, web services, database software, and other key software for application environments.
Integrity Measurement Architecture (IMA) can detect files that have been maliciously modified and assess the integrity of the Linux kernel. To validate the authenticity and integrity of the OS distribution, RHEL 9 supports IMA along with Extended Verification Module (EVM) to protect file-extended attributes. RHEL 9 Malware Detection, provided with Red Hat Insights, can perform a security assessment by using YARA pattern-matching software to show evidence of malware.
RHEL 9 also provides greater control over root-user password authentication using SSH. It is possible to disable root-user login with basic passwords to help Strengthen server security. Updated classes, permissions, and features of SELinux are part of RHEL 9 to leverage Linux Kernel security capabilities.
RHEL 9 also uses OpenSSL 3.0.1, which improves the cryptographic libraries and processes to Strengthen confidentiality and integrity of web communications.
Red Hat systems are often used in environments that require heightened levels of security and must meet certain security compliance requirements. Governments often require Security Technical Implementation Guide (STIG) configuration standards along with validation using Security Content Automation Protocol (SCAP). RHEL 9 supports OpenSCAP 1.3.6 and can use the SCAP Security Guide (SSG) and the RHEL 9 Open Vulnerability Assessment Language (OVAL) signatures to check for compliance.
Red Hat Insights is a management and operations service that reviews RHEL systems for compliance, vulnerabilities, patch, gain configuration advice, and optimization. Red Hat Insights Image Builder allows creation of custom RHEL images for simplified deployment to environments including cloud infrastructure.
Red Hat offers Image Builder as-a-Service to customize and standardize a preferred RHEL 9 image and run it in an IaaS cloud service provider. Image Builder can create blueprints to customize the bootable ISO installer image. The new version of Image Builder supports creation of separate logical filesystems. This helps when meeting security-compliance requirements that call for specific directories and file systems to use dedicated partitions for STIGs.
Web-based monitoring and administration tool Cockpit comes with RHEL 9, making management and operations easier for those new to Red Hat system management.
Red Hat emphasizes uptime and supportability while keeping systems patched. RHEL 9 supports kernel live patch management that allows patching a running Linux kernel without rebooting or restarting processes.
Red Hat systems often run in cloud environments. RHEL 9 includes Resource Optimization for cloud deployments to help size the system appropriately for its workload and to balance performance and costs.
The first step toward using RHEL 9 is installing it in a test environment to get to know how it works. The 60-day demo subscription can get you started. It is important to thoroughly test RHEL 9 before lifting and shifting workloads onto new RHEL 9 systems; upgrading in-place is discouraged.
Next, perform an asset inventory of all the RHEL systems in the environment. It’s okay to admit that there are some old RHEL 6 and 7 systems in the environment in desperate need of upgrades. Some organizations may even have a few RHEL 5 and CentOS 4 systems lurking about their data centers. Those older servers are ideal candidates for RHEL 9 upgrades.
Red Hat contributes to many open-source software projects, and CentOS Linux is their upstream source for RHEL. Check out CentOS Stream 9 (released December 3, 2021) to experience what features may be coming to RHEL 9.1.
If you want to check out the latest Linux features for free, the Fedora Project (now Fedora 36) may be something to get and install. Fedora is intended to have the most leading-edge features and provide a vision for the future progression of the RHEL OS. Red Hat is the primary contributor to the Fedora Project, but it also has worldwide community contributors.
Fedora Workstation 36 (released May 10, 2022) comes with the latest GNOME 42 desktop along with many other new features and software. Fedora 37 will be released in December 2022, an aggressive release schedule that promotes innovation and rapid evolution of new features.
Red Hat provides long-term support for customers who run production applications for many years and require the stability. It also publishes its release schedule and the support life cycle of the operating systems. The schedule had been for a new release every five years, but with RHEL 9 has returned to a three-year cadence. Dot releases occur annually, so RHEL 9.1 should be out around May 2023.
Support for major RHEL releases span 10 years, five years of full support followed by five years of maintenance. For example, RHEL 6 was released May of 2011 and is now in the Extended Life-cycle Support (ELS) phase for customers who purchase that Add-on subscription).
RHEL 9 won't enter the ELS phase until May 2032. It's hard to plan that far in advance, but Red Hat has a long tradition of honoring commitments to customers. Here is a diagram of the lifespan of RHEL 9 from the RHEL support matrix.
Based on the transparency of the release schedule and Red Hat’s history of meeting it, we can expect RHEL 10 to be out sometime in May 2025.
Copyright © 2022 IDG Communications, Inc.
Big Data Security Analytics , Next-Generation Technologies & Secure Development
Databand.ai Ensures Data Is Being Accessed by the Right Users at the Right TimeIBM has purchased a data observability startup to help organizations address data errors, pipeline failures and poor quality before it affects their bottom line.
The Armonk, New York-based technology giant says its acquisition of Tel Aviv, Israel-based Databand.ai will help businesses ensure that trustworthy data is being put into the hands of the right users at the right time. Databand.ai can alert data teams and engineers when the data they are using to fuel an analytics system is incomplete or missing, according to IBM.
"Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes," IBM Data and AI General Manager Daniel Hernandez says in a statement. "When they don't have access to the data they need in any given moment, their business can grind to a halt."
Terms of the acquisition - which closed June 27 and was announced Wednesday - weren't disclosed, though Israeli publication Globes reported that IBM paid $150 million for Databand.ai. An IBM spokesperson declined to comment on the purchase price reported by Globes. IBM's stock was up $0.46 - 0.33% - Wednesday to $138.08 per share.
Former Sisense Product Manager Josh Benamram founded Databand.ai in 2018 and has led the company since its inception. Databand.ai currently employs 51 people and in December 2020 closed a $14.5 million Series A funding round led by venture capital firm Accel, according to LinkedIn and Crunchbase (see: IBM to Buy Red Hat for $34 Billion).
"You can't protect what you can't see, and when the data platform is ineffective, everyone is impacted - including customers," Benamram says in a statement. "Joining IBM will help us scale our software and significantly accelerate our ability to meet the evolving needs of enterprise clients."
Becoming part of IBM will allow Databand.ai to fortify its observability muscle for broader integrations across more of the open-source and commercial offerings powering the modern data stack. Businesses will have the flexibility to run Databand.ai either as-a-service or as a self-hosted software subscription, according to IBM.
Databand.ai builds on IBM's existing Instana platform to provide a more complete and explainable view of the entire application infrastructure and data platform system. This can help organizations prevent lost revenue and reputation, according to IBM.
"Data observability takes traditional data operations to the next level by using historical trends to compute statistics about data workloads and data pipelines directly at the source, determining if they are working, and pinpointing where any problems may exist," Mike Gilfix, IBM's vice president of data and AI product management, writes in a blog post.
Gilfix says Databand.ai collects data pipeline metadata across key technology in the modern data stack and uses that to build historical baselines for data pipeline behavior. This allows Databand.ai to detect and generate alerts on anomalies while the data pipelines run as well as resolve anomalies in an automated fashion without affecting the delivery, according to Gilfix.
Databand.ai's technology will Strengthen mean time to discovery by detecting and executing on data pipeline issues in real time instead of reacting afterward, Gilfix says. Mean time to repair will also Strengthen since the contextual metadata provided by Databand.ai helps data engineers focus on the source of the problem rather than debugging where the issue stems from, according to Gilfix.
IBM will make Databand.ai's data observability capability available on a stand-alone basis, but Gilfix recommends using it alongside the company's multi-cloud data integration, data governance and privacy, and trustworthy AI capabilities to more effectively automate the data life cycle. Databand.ai will integrate with these other use cases for improved results where both are applied, according to Gilfix.
"Catching data quality problems at the source helps enable the delivery of more reliable data," Gilfix writes in the blog post. "Monitoring both static and in motion pipelines while delivering high quality metadata enables a faster time to value than would otherwise be possible."
Data observability platforms historically have been used to ensure an organization's data is clean and useful for downstream teams by probing for issues such as data lineage and algorithmic drift, Forrester Vice President and Principal Analyst Jeff Pollard tells ISMG. But security leaders are increasingly looking to get visibility into their organization's data to ensure that it isn't being tampered with by adversaries, he says.
Security and data leaders were each erroneously assuming that the other team was responsible for ensuring that data hadn't been tampered with, but Pollard says it's increasingly clear that CISOs have a role to play when it comes to data integrity. Pollard expects this to become a greater area of focus as businesses work to ensure adversaries aren't tampering with or poisoning their data.
"The more you automate things, the more you're relying on sensor data and input and things like that," Pollard says. "They've got motivation to have you make the wrong choice."
Investment activity around data observability has picked up over the past two to four years to ensure the integrity of the data that's increasingly being used in artificial intelligence and machine-learning algorithms, Pollard says. Data scientists typically understand what's being input into the algorithms, but Pollard says visibility and telemetry for those who aren't practitioners is limited due to closed systems.
Security teams were traditionally focused on understanding and correlating log data, but observability platforms tend to be much closer to the applications and data actually in question, according to Pollard. He therefore encourages security leaders to build programs, processes and practices around app and data observability pipelines in better alignment with practices across the organization.
"Security leaders need to keep their eyes focused on concepts around observability because this will be an area where they are starting to make sizable investments in the future," Pollard says. "And it's very much a change from what they've done in the past."
A new collaboration between The University of Tennessee at Chattanooga and IBM will provide students an array of marketable skills in data analytics, one of the fastest growing sectors in the national and regional economy. Smart technologies, cloud computing, mobile platforms, social media and other new generation technologies are fueling the revolution of big data.
According to IBM’s exact Tech Trends Report, only 1 in 10 organizations has the skills needed to effectively apply advanced technologies such as business analytics, mobile computing, cloud computing and social business.
In the U.S. alone, IT jobs are expected to grow by 22 percent through 2020 according to the US Bureau of Labor Statistics.As part of the UTC-IBM relationship, faculty have access to the resources in IBM’s Academic Initiative. This program provides access to technology, curriculum and learning materials at no cost for faculty members around the world. IBM has also provided advanced education for UTC faculty members, which has resulted in the development of curriculum, according to Dr. Joseph Kizza, Professor and Head of the Department of Computer Science and Engineering. Kizza is currently teaching the course Big Data Analytics using IBM software, including Cognos, BigInsights and InfoSphereStreams.
“The collaboration with IBM is already helping the program to prepare graduating students with the most up-to-date and in-demand skills in the industry. This is going to help our students get better and more paying jobs. In the process, this will eventually help our recruitment,” explained Kizza. “Additionally, we hold two Computer Science and Engineering (CSE) Showcases a year where we invite high school students to spend a Saturday with us and do hands-on labs. This opportunity will help us demonstrate the latest technologies in Big Data analytics, for example, which may increase or ignite students interests in attending UTC.”
BlueCross BlueShield of Tennessee, the city’s largest private employer, also collaborated by providing guidance on the curriculum and sharing insights on the real-world skills needed for success. The company believes the program will not only help meet its own need for technical talent, but provide a boost for the entire community.
“I see UTC becoming a leading academic institution for business analysis and data management—it will begin to produce the business intelligence experts Chattanooga companies need,” according to Brian Green, Manager of Business Intelligence and Performance Management at BlueCross. “Through this collaboration, local businesses will be able to tap into UTC’s academic offerings to make their companies more successful in critical new areas like Big Data analytics.”
He says students who take advantage of these opportunities can become “immediately marketable” in this fast-growing field. “They will graduate with hands-on experience in the IBM tools commonly used in the workplace.”
Mr.Green, who graduated from UTC in 1980, has been in the business of information management and system development in the insurance industry for more than 30 years.
“UTC has been involved in the IBM Academic Skills Cloud pilot program and we are proud to support the university’s efforts to provide students with data-driven education,” said Dan Hauenstein, director, IBM Academic Initiative. “Through the IBM Academic Initiative, students and faculty have access to industry leading technology and courseware to help develop the advanced big data analytics skills needed for jobs of the future.”
IBM’s Academic Initiative provides no charge access to curriculum, software and learning materials to more than 30,000 faculty members around the world.
IBM is acquiring Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including errors, pipeline failures, and poor quality. The acquisition further strengthens IBM's software portfolio across data, AI, and automation to address the full spectrum of observability.
Databand.ai is IBM's fifth acquisition in 2022 as the company continues to bolster its hybrid cloud and AI skills and capabilities.
Databand.ai's open and extendable approach allows data engineering teams to easily integrate and gain observability into their data infrastructure.
This acquisition will unlock more resources for Databand.ai to expand its observability capabilities for broader integrations across more of the open source and commercial solutions that power the modern data stack.
Enterprises will also have full flexibility in how to run Databand.ai, whether as-a-Service (SaaS) or a self-hosted software subscription.
The acquisition of Databand.ai builds on IBM's research and development investments as well as strategic acquisitions in AI and automation. By using Databand.ai with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations.
"Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes. When they don't have access to the data they need in any given moment, their business can grind to a halt," said Daniel Hernandez, general manager for data and AI, IBM. "With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale."
The acquisition of Databand.ai further extends IBM's existing data fabric solution by helping ensure that the most accurate and trustworthy data is being put into the right hands at the right time—no matter where it resides.
Headquartered in Tel Aviv, Israel, Databand.ai employees will join IBM Data and AI, further building on IBM's growing portfolio of Data and AI products, including its IBM Watson capabilities and IBM Cloud Pak for Data. Financial details of the deal were not disclosed. The acquisition closed on June 27, 2022.
For more information about this news, visit www.ibm.com.
“AWS (US), Google (US), Microsoft (US), IBM (US), Alibaba Cloud (China), Oracle (US), Rackspace Technology (US), HPE (US), Dell Technologies (US), Dropbox (US), Box (US), Tencent Cloud (China), Fujitsu (Japan), VMware (US), NetApp (US), Hitachi Vantara (US), Scality (US), Citrix (US), UpCloud (Finland), Huawei (China), DigitalOcean (US), Vultr (US), MinIO (US).”
Cloud Storage Market by Component (Solutions and Services), Application (Primary Storage, Backup and Disaster Recovery, and Archiving), Deployment Type (Public and Private Cloud), Organization Size, Vertical and Region – Global Forecast to 2027
The Cloud Storage Market size is expected to grow from USD 78.6 billion in 2022 to USD 183.7 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 18.5% during the forecast period. The demand for cloud storage is driven by emerging data volumes across enterprises, evolving requisite for provision of the remote workforce with ubiquitous access to data and files, and cost-saving and low Total Cost of Ownership (TCO) benefits of cloud storage solutions.
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The services component grow at a higher CAGR during the forecast period
Services play a crucial role in the cloud storage market as these services help before and after the deployment of cloud storage solutions to the clients. Service providers assist their clients in various phases, such as planning, deploying, maintaining, and upgrading cloud storage solutions. The following chapter explains the importance of cloud storage services, such as consulting; integration and implementation; and training, support, and maintenance.
Backup and Disaster recovery segment to grow at the highest CAGR during the forecast period
Backup and disaster recovery applications protect enterprise application data during disasters. They enable customers and enterprises to store and run their systems on the cloud, reduce costs, accelerate the recovery process, and free up resources for other important tasks. These solutions are gaining popularity as they are more reliable and save enterprises the task of maintaining the costly hardware infrastructure needed for backup and disaster recovery. The use of mock drill platforms for disaster recovery enables the addition of resources that can be deployed online in the event of a disaster; this further reduces the recovery time after a major failure. The benefits offered by disaster recovery and backup solutions include data synchronization, online viewing, and easy accessibility.
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The major players in the cloud storage market are AWS (US), Google (US), Microsoft (US), IBM (US), Alibaba Cloud (China), Huawei (China), Oracle (US), Rackspace Technology (US), HPE (US), Dell Technologies (US), Dropbox (US), Box (US), Tencent Cloud (China), Fujitsu (Japan), VMware (US), NetApp (US), Hitachi Vantara (US), Scality (US), and Citrix (US). These players have adopted various growth strategies, including new product launches, partnerships, agreements, mergers and acquisitions, and business expansions. Product enhancements, business expansions, and partnerships were the major strategies adopted by these players to achieve a strong foothold in the cloud storage market.
IBM is one of the leading providers of cloud platform services and cognitive solutions, which works across domains such as cloud, IT infrastructure, security, services, and research. The company operates in more than 175 countries and caters to industries worldwide. The company functions through six main segments: Global Technology Services, Cloud and Cognitive Software, Global Business Services, Systems, Global Financing, and Other. IBM offers infrastructure, hosting, and consulting services in customer relationship management, business analytics optimization, outsourcing, software, and security. The company is focused on developing solutions and products powered by the latest technologies, including AI and ML, analytics, big data, and IoT. The company also offers services to help clients transform their businesses, and the service portfolio comprises application services, security, Business Processes and Operations (BPO), cloud services, digital workplace services, and more.
Microsoft’s, one among the leading Cloud storage solutions and service providers, major cloud offerings include SaaS (Microsoft Dynamics Online [Enterprise Resource Planning (ERM) + CRM] and O365 Online), and IaaS and PaaS (Microsoft Azure [compute, integration, and networking]). Microsoft has invested heavily in managed services for hybrid cloud, IoT, and edge computing platforms. Innovations, such as Azure Sphere, Digital Twins, and Azure IoT Central, have placed Microsoft ahead of its competition in the IIoT and edge computing industries. The company introduced Azure Edge Zones, a convergence of cloud managed services, hardware, and high-speed 5G networks. In the cloud storage market, Microsoft offers the Microsoft Azure Storage platform, a cloud storage solution that encompasses various data storage services, including Azure Blobs, a scalable object store for text and binary data; Azure Files, a managed file sharing service for cloud deployments; Azure Queues, a messaging store for messaging between application components; Azure Tables: a NoSQL store for schema-less storage of structured data; Azure Disks, block storage volumes for Azure VMs.
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Acquisition helps enterprises catch “bad data” at the source
Extends IBM’s leadership in observability to the full stack of capabilities for IT -- across infrastructure, applications, data and machine learning
ARMONK, N.Y., July 6, 2022 /PRNewswire/ -- IBM (NYSE: IBM ) today announced it has acquired Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including errors, pipeline failures and poor quality — before it impacts their bottom-line. Today’s news further strengthens IBM’s software portfolio across data, AI and automation to address the full spectrum of observability and helps businesses ensure that trustworthy data is being put into the right hands of the right users at the right time.
Databand.ai is IBM’s fifth acquisition in 2022 as the company continues to bolster its hybrid cloud and AI skills and capabilities. IBM has acquired more than 25 companies since Arvind Krishna became CEO in April 2020.
As the volume of data continues to grow at an unprecedented pace, organizations are struggling to manage the health and quality of their data sets, which is necessary to make better business decisions and gain a competitive advantage. A rapidly growing market opportunity, data observability is quickly emerging as a key solution for helping data teams and engineers better understand the health of data in their system and automatically identify, troubleshoot and resolve issues, like anomalies, breaking data changes or pipeline failures, in near real-time. According to Gartner, every year poor data quality costs organizations an average $12.9 million. To help mitigate this challenge, the data observability market is poised for strong growth.1
Data observability takes traditional data operations to the next level by using historical trends to compute statistics about data workloads and data pipelines directly at the source, determining if they are working, and pinpointing where any problems may exist. When combined with a full stack observability strategy, it can help IT teams quickly surface and resolve issues from infrastructure and applications to data and machine learning systems.
Databand.ai’s open and extendable approach allows data engineering teams to easily integrate and gain observability into their data infrastructure. This acquisition will unlock more resources for Databand.ai to expand its observability capabilities for broader integrations across more of the open source and commercial solutions that power the modern data stack. Enterprises will also have full flexibility in how to run Databand.ai, whether as-a-Service (SaaS) or a self-hosted software subscription.
The acquisition of Databand.ai builds on IBM’s research and development investments as well as strategic acquisitions in AI and automation. By using Databand.ai with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations.
For example, Databand.ai capabilities can alert data teams and engineers when the data they are using to fuel an analytics system is incomplete or missing. In common cases where data originates from an enterprise application, Instana can then help users quickly explain exactly where the missing data originated from and why an application service is failing. Together, Databand.ai and IBM Instana provide a more complete and explainable view of the entire application infrastructure and data platform system, which can help organizations prevent lost revenue and reputation.
“Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes. When they don’t have access to the data they need in any given moment, their business can grind to a halt,” said Daniel Hernandez, General Manager for Data and AI, IBM. “With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale.”
Data observability solutions are also a key part of an organization’s broader data strategy and architecture. The acquisition of Databand.ai further extends IBM’s existing data fabric solution by helping ensure that the most accurate and trustworthy data is being put into the right hands at the right time – no matter where it resides.
“You can’t protect what you can’t see, and when the data platform is ineffective, everyone is impacted –including customers,” said Josh Benamram, Co-Founder and CEO, Databand.ai. “That’s why global brands such as FanDuel, Agoda and Trax Retail already rely on Databand.ai to remove bad data surprises by detecting and resolving them before they create costly business impacts. Joining IBM will help us scale our software and significantly accelerate our ability to meet the evolving needs of enterprise clients.”
Headquartered in Tel Aviv, Israel, Databand.ai employees will join IBM Data and AI, further building on IBM’s growing portfolio of Data and AI products, including its IBM Watson capabilities and IBM Cloud Pak for Data. Financial details of the deal were not disclosed. The acquisition closed on June 27, 2022.
To learn more about Databand.ai and how this acquisition enhances IBM’s data fabric solution and builds on its full stack of observability software, you can read our blog about the news or visit here: https://www.ibm.com/analytics/data-fabric.
About Databand.ai
Databand.ai is a product-driven technology company that provides a proactive data observability platform, which empowers data engineering teams to deliver reliable and trustworthy data. Databand.ai removes bad data surprises such as data incompleteness, anomalies, and breaking data changes by detecting and resolving issues before they create costly business impacts. Databand.ai’s proactive approach ties into all stages of your data pipelines, beginning with your source data, through ingestion, transformation, and data access. Databand.ai serves organizations throughout the globe, including some of the world’s largest companies in entertainment, technology, and communications. Our focus is on enabling customers to extract the maximum value from their strategic data investments. Databand.ai is backed by leading VCs Accel, Blumberg Capital, Lerer Hippeau, Differential Ventures, Ubiquity Ventures, Bessemer Venture Partners, Hyperwise, and F2. To learn more, visit www.databand.ai.
About IBM
IBM is a leading global hybrid cloud and AI, and business services provider, helping clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,800 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently, and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity, and service. For more information, visit www.ibm.com.
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1 [1] Source: Smarter with Gartner, “How to Strengthen Your Data Quality,” Manasi Sakpal, [July 14, 2021]
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
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SOURCE IBM
SAN RAMON, Calif., June 21, 2022 /PRNewswire/ -- eCIFM Solutions Inc. (eCIFM®) IBM Gold-Accredited IBM business partner and developer of eCIFM On The Go! mobile applications, is pleased to announce that it was awarded a multi-year contract to enhance and support an IWMS system for the Judicial Council of California.
The Council conducted a comprehensive RFP (Request for Proposal) process that attracted interest from world-class organizations, ultimately selecting eCIFM® for their extensive TRIRIGA experience, longevity and deep bench of development, consulting, and support resources. The project scope entails remediation, upgrade and implementation of additional modules and features to support the Council's processes and requirements. After the upgrade of TRIRIGA, eCIFM will then move the upgraded environment from the Council's current hosted environment to the IBM FedRAMP SaaS cloud, which will also include the database conversion to DB2. eCIFM will then begin a multi-year engagement to provide on-going TRIRIGA support and maintenance for the Council's IWMS system.
About The Judicial Council of CaliforniaThe Judicial Council of California is the policymaking body for California's judicial branch, the largest court system in the United States. To carry out its' functions, the Council has an extensive and varied portfolio of over 800 properties and is both a tenant and a landlord. Buildings range from courts to administrative offices and are located throughout the state of California.
About eCIFM Solutions Inc.eCIFM® is a Systems Integrator for all leading IWMS applications. Founded in 2000, eCIFM is a Gold-Accredited IBM TRIRIGA Business Partner and an iOFFICE, Nuvolo, ServiceNow and Archibus Business Partner, providing services for organizations looking to Strengthen their real estate portfolios and workplace management. eCIFM® is the developer of the patented On The Go! (OTG!) suite of mobile applications for Facilities Management, used by hundreds of mobile technicians across a variety of industries. eCIFM® is a global company with offices in USA, Australia, Hong Kong and India. Verdantix, an independent analyst research firm, featured eCIFM Solutions as one of the top 13 system integrators for IWMS in the world. Verdantix recognized eCIFM for "a unique IWMS platform and mobile implementation package" in their 2021 Green Quadrant Report.
Media Contact:
Kelly Vento, Marketing Manager
eCIFM Solutions Inc.
kelly.vento@ecifm.com
(925) 830-1925
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www.ecifm.com
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SOURCE eCIFM Solutions Inc.
The Qatar Public Works Authority 'Ashghal' has awarded IBM the contract to provide a smarter road and drainage infrastructure in the gas-rich country.
The new system will enhance the quality of services, safety and environmental sustainability for citizens in the country.
In line with the Qatar National Vision 2030, Ashghal and IBM will deploy an Enterprise Asset Management Solution (EAMS) to effectively manage the operation and maintenance of the country's roads and drainage networks and multiple effluent and water treatment plants.
The solution will enable Ashghal to rapidly evaluate and respond to defects or incidents reported by citizens and anticipate and prevent problems. Enabled through the use of mobile devices,
Ashghal will be able to quickly plan work requirements, determine resource availability and ensure the right crew responds with the right materials and tools.
The new system will also gather and analyse millions of discrete pieces of information about the country's road and drainage assets through a Geographic Information System (GIS) to allow the location of assets or work to be determined and tracked in real time.
During the project kick-off meeting Ashghal's president Nasser bin Ali Al Mawlawi said the implementation of EAMS is a pivotal step towards enhancing and streamlining the services of Ashghal's roads and drainage operations and maintenance departments.
"Designed with a focus on customer centricity, the solution will help Ashghal to advance its asset management services with the organisation's overall business goals through a system that will certain lower asset failure frequency and ensure timely maintenance. With this advanced software, Ashghal will gain real time visibility into the country's asset usage and, better govern and manage the lifecycle of road and drainage networks to achieve higher returns on national investment," he added.
According to him, the ability to draw from multiple sources across Qatar will also provide better insight into the condition of pipes buried deep underground in specific locations and the road network.
"This will help reduce the frequency of maintenance interventions, which in turn will help reduce traffic congestion and increase public safety. It will ensure the road and drainage systems are safer and environmentally sustainable," he added.
With a total land area of 11,500 sq km and a population of 2.2 million, Qatar has experienced rapid economic growth over the last several years. This economic growth has resulted in increased demand for government entities in Qatar to provide a world-class infrastructure.
IBM opened an office in Qatar in April 2012 as part of the company's expansion in the Middle East to meet the growing needs of customers in the region.
"Building a smarter infrastructure is the foundation to establishing a smarter economy. Citizens are also placing increasing demands on their leaders to innovate and progress," remarked Amr Refaat, the general manager, IBM Middle East and Pakistan.
"The roll out of the Enterprise Asset Management Solution is a key demonstration of how Ashghal is already executing on Qatar's journey to a smarter economy leveraging Smart City concepts and enhancing citizen services," he added.
Based on IBM's Maximo Asset Management Software, the solution will transform the way road and drainage asset data, maintenance work, and ultimately customer services are managed within the Authority's Asset Affairs operations.