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Exam Code: A2010-538 Practice exam 2022 by team
Assess: IBM Tivoli Monitoring V6.2.2 Implementation
IBM Implementation information
Killexams : IBM Implementation information - BingNews Search results Killexams : IBM Implementation information - BingNews Killexams : IBM and AWS Create a Path to Modernization Via Industry-Specific Solutions No result found, try new keyword!Industry-specific solutions in development cover verticals including manufacturing, financial services, healthcare, and transportation. Wed, 12 Oct 2022 13:27:00 -0500 en-US text/html Killexams : 20.5% CAGR for Incident Response Services Market No result found, try new keyword!Global Incident Response Services Market is valued at USD 19.47 Billion in 2021 and expected to reach USD 71.82 Billion by 2028 with a CAGR of 20.5% over the forecast period. Incident Response ... Mon, 17 Oct 2022 04:39:00 -0500 en-US text/html Killexams : 20.5% CAGR for Incident Response Services Market Revenue Worth $71.82 Billion, Globally, by 2028 - Exclusive Research No result found, try new keyword!Global Incident Response Services Market is valued at USD 19.47 Billion in 2021 and expected to reach USD 71.82 Billion by 2028 with a CAGR of 20.5% over the forecast period. Incident Response ... Mon, 17 Oct 2022 04:37:00 -0500 en-US text/html Killexams : ForgeRock, Ping, IBM, Okta Top KuppingerCole CIAM Tech Eval

Customer Identity & Access Management (CIAM) , Security Operations

Consumerization of IT Has Brought CIAM Methods, Technologies to Workforce IAM Space
ForgeRock, Ping, IBM, Okta Top KuppingerCole CIAM Tech Eval

Perennial leaders ForgeRock, Ping Identity and IBM, along with a surging Okta, set themselves apart from the pack of CIAM vendors in the latest report by KuppingerCole analysts.

See Also: Building a Secure IoT Deployment Using 5G Wireless WAN

Ping Identity leapfrogged ForgeRock to capture the gold in product leadership, and IBM once again took the bronze. ForgeRock, Ping Identity and IBM maintained the gold, silver and bronze, respectively, in innovation leadership. And in the market leadership category, Microsoft again took gold, Auth0 catapulted from seventh to second place in market leadership due to becoming part of Okta, and SAP fell from second to third since the last report in late 2020, KuppingerCole found.

"The trend toward digitalization of consumer experiences was well underway in the late 2010s, and the COVID pandemic forced more businesses and other organizations to expedite digital transformation," John Tolbert wrote in the 120-page report. "With every iteration of this report, we observe significant acquisitions of CIAM certified by others in the market, and entry into the market of new vendors."

Microsoft, Okta and IBM were the three market share leaders in the broader $13.6 billion identity and access management category last year, while Ping Identity and ForgeRock captured ninth and 10th place, according to IDC. Thoma Bravo has acquired SailPoint and plans to buy Ping and ForgeRock. Should the three companies be combined, it would take the bronze in market share, narrowly edging out IBM.

"Innovation in CIAM drives the wider IAM market," Tolbert wrote. "The 'consumerization of IT' is exemplified by the push to use CIAM methods and technologies for registration, authentication, and authorization in workforce IAM. Features that were considered innovative in the previous edition of this report are going mainstream."

Outside of the top four, here's how KuppingerCole sees the CIAM market:

  • Leader: SAP, LoginRadius, Microsoft, Transmit Security, OneWelcome, WSO2;
  • Challenger: Cisaas, Cloudentity, Optimal IDM, 1Kosmos, Simeio, Synacor, CoffeeBean, Xayone, Nevis Security, NRI, ReachFive, Fusion Auth, DruID.

The latest rankings represent a drop for SAP and WSO2, which fell from third to fifth and eighth to 10th, respectively. Microsoft and OneWelcome leapt from ninth to seventh and 10th to ninth, respectively. LoginRadius held steady in sixth place, while Transmit Security - which raised $543 million last year - is new to the list.

"The CIAM market is growing and there is room for much further expansion, with many vendors offering mature solutions providing standard and deluxe features to support millions of users across every industrial sector," Tolbert wrote. "Some vendors have about every feature one could want in a CIAM product, while others are more specialized, and thus have different kinds of technical capabilities."

How the CIAM Leaders Climbed Their Way to the Top

Company Name Acquisition Amount Date
ForgeRock None N/A N/A
IBM Lighthouse Security Group Not Disclosed August 2014
Okta Auth0 $5.67B May 2021
Ping Identity UnboundID Not Disclosed August 2016

ForgeRock Looks to Thwart Account Takeover Fraud

ForgeRock in April refreshed the user interface around its authentication app to Boost the customer experience, add functionality for facial biometrics, and leverage capabilities from Apple and Android, according to CEO Fran Rosch. He says ForgeRock has sought smarter ways to identify legitimate users and deliver them access by leveraging AI to collect signals of typical user and device behavior.

Once ForgeRock has collected patterns around a typical positive user experience, the company develops a risk score to deliver customers more confidence about whether a legitimate user is attempting to log in. To prevent account takeover fraud, ForgeRock has factored in both known threats and threats projected via AI into its risk score and has incorporated more information about device behavior into its app (see: Thoma Bravo Identity Push Continues With $2.3B ForgeRock Buy).

"CIAM has got a strong security component, but also a strong usability component," Rosch tells Information Security Media Group. "And we've always worked to embed that capability of self-service and ease of use into the platform."

KuppingerCole criticized ForgeRock for implementation challenges around the on-premises version and a lack of native marketing analytics, marketplace integrations and certification around FIDO. Rosch says ForgeRock has focused on simplifying the deployment of its on-premises offering by crafting DevOps capabilities for implementation, simplifying upgrades and creating new configurable AI for the platform.

"Every company's got room to improve," Rosch says. "Generally, we would agree with those areas identified by KuppingerCole. We're continuing to work and to improve."

Ping Identity Embraces CIAM in the Cloud

Over the past five years, Ping Identity has migrated all of its core capabilities to the cloud, meaning customers don't have to deal with infrastructure, management or upgrades and can focus on the user experience, says Dustin Maxey, vice president of product and solutions marketing. Having everything available as a multi-tenant, SaaS-based offering means Ping can support customers' various deployment options, he says.

Maxey says Ping has defined and developed workflows for CIAM scenarios such as account registration and fraud detection that incorporate both native and third-party capabilities and are easy for customers to use. Over the past year, Ping has made real progress on decentralized identity and combining multiple fraud signals in one place so that risk and fraud can be assessed at the point of authentication, he says (see: Ping Identity to Go Private in $2.8B Thoma Bravo Acquisition).

"A lot of competitors will have orchestration platforms, but Ping really differentiates in that we fully embrace this open mentality," Maxey tells ISMG. "If you want to use competitive services - if you want to use ForgeRock authentication or Okta authentication - we can plug that authentication service into our orchestration platform that we created."

KuppingerCole criticized Ping for its inability to collect device attributes, customization requiring for consent handling, and lack of simple connectors for BI, CRM, marketing analytics and automation. Maxey says Ping has focused on building the most important connectors first and wants to create deep integrations within its existing connectors before pivoting to construct new connectors.

"We are on a tear to build connectors that are deep, that are numerous and that are the ones that represent the services that our customers work with," Maxey says. "And we are moving very, very fast at that."

IBM Ensures Legacy Apps Don't Get Left Behind

IBM has actively participated in committees and bodies that manage protocol support to help clients better manage API and authentication requests in applications, says Wesley Gyure, director of product management for IBM Security. Offering support for both old and new protocols gives clients a seamless experience across apps in legacy infrastructure as well as modern web-based applications in the cloud.

Gyure says the company has integrated its CIAM offering with threat intelligence to get more visibility into everything from compromised passwords to potential malicious account takeover and the opening of fraudulent accounts. Identity threat detection and response starts with determining whether to block or challenge a registration request based on if the IP address is known and if the device could be malicious (see: IBM Buys Startup to Address Data Quality Issues).

"We have very large Fortune 500 clients that are using our systems, both legacy and off-prem," Gyure tells ISMG. "Auto manufacturers, retail, state and local government - they all have millions of users that are authenticating to our system, and they're doing so in a frictionless way and they're doing so with high throughput."

KuppingerCole chided IBM for complicated licensing, limited configurations for family management, and no built-in identity proofing or out-of-the-box consumer device management portals. The complexity stems from thousands of customers already using CIAM in large deployments, and Gyure says a pricing calculator for the latest tools should deliver clients visibility and transparency into how IBM licenses.

"We're not going to be the experts in every area," Gyure says. "Customers already have investments in solutions that they're using, and those investments have to integrate into whatever CIAM solution they may choose. This is not a rip-and-replace conversation. We want to make this easy and consumable, and to do that means to leverage capabilities and investments that they may already have."

Okta Scales Authentication to the Masses

Okta has made strides to enable app builders to better manage user authentication at scale by enabling developers to add another layer of access controls that's more fine-grained and consistent across apps, says Matt Duench, senior director of product marketing. The company's flow editor allows for no-code integration with firms such as Duo directly into the platform by leveraging a drag-and-drop interface.

Duench says the company has debuted a deployment option in Microsoft Azure so that customers in Europe and elsewhere can deploy in the environment that makes the most sense for them. Okta has strengthened its account takeover prevention capability through investments in Credential Guard and has reduced bot attacks by 79% by incorporating machine-learning upgrades in its bot detection engine (see: Okta-Auth0 Sales Integration Falters, Fueling Staff Turnover).

"We were born in the cloud, and so we're really well suited for companies that are focused on digital transformation and cloud migration versus more of an on-prem system," Duench tells ISMG. "And that's because a lot of the flexibility that now you get from a cloud-based system you can get within our platform as well."

KuppingerCole criticized Okta for a lack of built-in behavioral biometrics, FIDO certification, and ability to collect device intel via mobile SDK. Okta says there are regulatory, privacy and technology constraints around capturing device intel via mobile SDK in consumer applications and that the company chose to allow customers to integrate Okta's CIAM tool with the behavioral biometrics technology of their choice.

"You need a cloud-based platform that is extensible, that is unified and that is neutral so that you can really allow the application builder to build those use cases in the way and using the methodologies that they're traditionally used to," Duench says.

Thu, 13 Oct 2022 11:59:00 -0500 en text/html Killexams : The Four Pillars To AI Innovation: How Businesses Can Jumpstart The AI Journey

By Anand Mahurkar, CEO, Findability.Sciences.

Rapid technological advances are changing how people do business—especially in post-pandemic times. Currently, the demand is for AI technology. PwC reported that "AI could contribute up to $15.7 trillion to the global economy in 2030" and will continue to be a game-changer by enabling organizations to increase productivity and consumption.

All businesses—be it healthcare, manufacturing, hospitality and even entertainment—are adopting AI to offer deep insight into their business processes and provide leading indicators that can help an organization prosper. To fully appreciate how AI is shaping the game, let’s look at some stats:

• In 2020, the AI in banking worldwide market was worth nearly $4 billion. By 2030, it's expected to be valued at over $64 billion.

• AI in healthcare was valued at $7.9 billion in 2021 and is predicted to grow to $201.3 billion by 2030.

Although these numbers are promising, it’s important to note that for a business to succeed in its AI journey, the organization needs to be ready for AI innovation. This means working on its IA—infrastructure architecture—before the real AI. Doing otherwise can lead the venture to fall to the wayside. According to Gartner analysts, "85% of AI and machine learning projects fail to deliver, and only 53% of projects make it from prototypes to production."

One major roadblock to a successful AI implementation is that although organizations usually have petabytes of data, the data is often unorganized, uncleaned and unanalyzed and sitting in a number of systems from ERP to CRM. Often, organizations simply don't have the right infrastructure or expertise to make sense of it.

For AI programs to work, data needs to be collected, cleaned and analyzed. However, the reality is that 82% of organization leaders say that data quality hinders their data integration projects and that they spend too much time on data cleaning, integration and preparation.

The goal for AI solution providers should be to help businesses become data-driven so that enterprises can utilize AI to the fullest in order to drive insights and predictions. AI solution providers can work with enterprises on these obstacles by keeping these four pillars in mind: creating a center of excellence and a collaborative AI team, prioritizing data modernization, embracing cloud transformation and leveraging partnerships.

1. Create a center of excellence.

Solutions providers should team up with a company’s internal employees, train or mentor the company’s representatives on the AI program and create their own center of excellence (CoE). Although the team might include data scientists or IT professionals, the CoE can also include marketing executives, end users, consumers and statisticians—all the minds required for collaboration. Consider the domain knowledge, understanding of customers and customer data, technology know-how and interpretation of data. The organization can work with its AI solution provider to create a roadmap as a guide on what benefits AI can provide in each area.

Each team member should be carefully selected based on the requirements and expertise a business needs. They should not only immerse themselves into the project but also maintain the company culture, as well as work according to the strategic goals.

2. Prioritize data modernization.

Organizations need information assets before AI. Creating a data architecture around an organization’s data assets is a critical next step. The newly formed team, along with the solutions provider, should handle this. They will have to determine which data should be collected and create an information architecture that can be utilized for AI purposes.

The first order of business should be how to collect data, which includes identifying data silos. It’s also necessary to utilize "wide data," or data coming from a variety of sources—internal and external as well as both structured and unstructured. "Big data" needs to be collected, too, or massive data coming at great speed.

The next step is to determine the processes and use cases the new data architecture can support. The team should keep in mind end-to-end migration services with automation that can take the company from planning to execution.

3. Embrace cloud transformation.

I highly suggest that businesses and customers today make the switch to cloud services. Many organizations are still utilizing legacy and on-premises technologies to store data. The cloud is now the better option when creating an AI framework. It lessens the bulk of hardware and also allows an organization to access the AI system from any device without further installations and processes. If data is still stored on physical servers, they just need to be migrated to secured cloud servers.

4. Leverage partnerships.

Although big organizations usually have licenses with IBM Cloud Pak or Snowflake, their stumbling block to a successful AI journey is that they don’t always know how to utilize these tools for AI implementation. The challenge is connecting the dots—utilizing third-party services for existing internal machines or data to create a prediction engine.

In addition, many popular warehousing or other big data technologies don't necessarily have AI plugins or prediction engines. The AI team should be tasked with the challenge of creating a system that uses the licenses or partnerships the company has for the solution they want to have. The AI solution provider must build that bridge that gets them to the finish line.

The reality is that the AI journey can be filled with potholes. There's a large amount of data sitting in an organization's system, ready for harnessing but often siloed by disparate teams. Other issues are that many companies are already invested in technology that can't be utilized for AI and, sometimes, the knowledge isn't there on how to leverage existing licenses and technologies for AI purposes.

The key to guiding companies in AI innovation is to let them visualize the possibilities and remind executive leaders that technology is advancing quickly, and AI is now typically considered a must-have asset for business sustainability. So, use these pillars and present the potential of an AI-driven enterprise.

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

Mon, 10 Oct 2022 02:15:00 -0500 Anand Mahurkar en text/html
Killexams : Findability Launches Findability.Accelerate to Assist Enterprises with AI Implementation

BOSTON, Sept. 21, 2022 — Findability Sciences, a global provider of enterprise AI solutions and an Inc. 5000 company, today announced the launch of Findability.Accelerate, which provides the tools and framework necessary to equip enterprises to become ‘AI-ready’ and expedite their AI journey. The demand for AI tech has surged in the post-pandemic world; PwC reported that AI is estimated to contribute up to $15.7 trillion to the global economy by 2030 and change the game by emphasizing productivity and consumption.

Anand Mahurkar, CEO of Findability Sciences

The challenge is that most organizations do not have a sound data architecture in place for successful AI implementation. In fact, the latest research has shown that up to 60% of AI projects fail. Organizations require that data is cleaned, analyzed and organized, but too often, enterprises are struggling with data overload and crippling silos that can hinder digital transformation. Findability.Accelerate mitigates this risk by providing an information architecture (IA) or IA (data) powered by products and solutions built on all major data platforms to ease migration. In addition, the platform also offers a customized comprehensive report to unify data for AI, as well as provides plugins for data migration and machine learning.

“There is no AI without IA,” said Anand Mahurkar, CEO of Findability Sciences. “The promise of artificial intelligence transforming businesses is appreciated by leadership across industries. However, the way AI is looked at, thought about, adopted and used, can only succeed with the right framework in hand. With the skills, processes and technology that Findability.Accelerate offers, an organization can successfully optimize data and succeed in its AI journey.”

Findability.Accelerate offers a three-pronged approach for an expedient and efficient enterprise AI implementation:

Information Architecture

Information architecture is the foundation on which data is organized and structured across a company. Findability.Accelerate addresses data gaps and silos with a Data Census designed to identify business processes, data sets, personally-identifiable information, third-party data and applications.

Findability.Accelerate uses a “Wide Data” approach to locate critical and relevant internal, external, structured and unstructured data for Machine Learning. The solution leverages connectors to over 40,000 external variables while implementing the information architecture to include relevant external data in the unified information.

Once the organization has successfully collected internal and external data, the framework can be built to create a solution, like a prediction engine that can also become part of an organization’s IP.

Platform Strategy

Findability.Accelerate has developed plug-and-play solutions for industry-leading platforms such as IIAS (IBM Integrated Analytics Systems), Snowflake, SAP, EDB, Amazon Redshift, DB2, Netezza, Automation Anywhere and AWS. Findability.Accelerate manages end-to-end migration of services with automated tooling to allow businesses to journey from planning to execution and advance the AI journey.

Through its partnership with industry-leading data platforms, Findability.Accelerate offers all the technology, skills and expertise required to enable businesses to migrate to modern, cloud-based data storage solutions.

Beyond data migration, Findability Sciences partner AI plugins provide access to a high-accuracy self-learning multi-modeling engine that can rapidly deploy solutions such as demand forecasting, propensity to pay and churn prediction on the unified data.

Technology Talent

Findability.Accelerate consists of professionals who are experts in managing AI applications, including monitoring, health checking, and maintaining the solutions program. Organizations without an IT staff can seek the help of the highly-skilled and cost-effective in-house tech talent of Findability Sciences staff augmentation services.

Every team member is partnered with an organization based on the organization’s specific business needs. The staff not only fully immerse themselves into the project, they also maintain a good company culture and work according to specific goals.

About Findability Sciences

Findability Sciences, an Inc. 5000 company, is a leading Enterprise AI Company that helps businesses worldwide realize the potential of data and become data superpowers. Findability Sciences enables customers across industries and geographies to accelerate their Data-to-AI Journey, enabling them to build their own IP and data science capabilities besides executing strategically to derive real financial ROI.

Source: Findability Sciences

Wed, 21 Sep 2022 07:45:00 -0500 text/html
Killexams : Insights-As-A-Service Market to grow at a rate of 23.4% by [2021-2031] | Get Customized Reports

Future Market Insights (FMI) has recently published data showing that from 2021 to 2031, the market for insights-as-a-service will see an increase in demand at a CAGR of 23.4%. By the end of 2021, the market is expected to be worth more than US$ 2.5 billion, according to the report. Rapid technological advancements and greater adoption of cloud computing across numerous organizations, according to FMI analysis, have opened up opportunities for the implementation of insights-as-a-service solutions.

Offerings for insights-as-a-service include data on stocks, finances, the performance of keywords, employee information, and business processes. Having access to this data enables businesses to make wise decisions. In addition, it aids in the identification of potential threats shortly.

Key Takeaways: Insights-as-a-service Market

  • By solution, the insights-as-a-service platform (SaaS-based) segment is anticipated to account for the leading share in the global market during the forecast period. The segment is estimated to grow at a robust CAGR of 24.3% through 2031.
  • The demand for insights-as-a-service solutions in small and medium enterprises (SMEs) is expected to rise at maximum pace as these organizations continue adopting cloud-based solutions for better ROI.
  • Demand for customer analytics platforms is estimated to grow at an impressive CAGR, as SMEs exhibit high demand for improved customer lifecycle management.
  • North America is expected to lead the market followed by Europe in 2021. South Asia & Pacific is anticipated to emerge as the fastest growing region between 2021 & 2031.
  • The market in India is expected to progress at a CAGR of 30.6% through 2031.
  • In the GCC Countries, sales are expected to increase at a CAGR of close to 19.0% over the next ten years.

Who is Winning?

Competition in the market is expected to intensify with the entry of new players. The emergence of new startups such as Atlan, testing, Beagle, Zume, Ritual, Coda, Bird, and others will drive the insights-as-a-service market shortly.

As per insights from KDNuggets, the investments towards other cloud-based and Insights-as-a-Service offerings is expected to increase to 35% from 15% by 2021 owing to stringent government rules and regulation to promote startups in the developed as well as developing countries.

This is expected to encourage key players to focus on the expansion of their global footprint. Some of the leading companies operating in the market are Capgemini, GoodData, GAVS Technologies, Oracle Corporation, and IBM Corporation among others.

Insights-as-a-service Industry Survey by Category


  • Insights-as-a-Service Platform (SaaS-based)
  • Services
    • Consulting & Advisory
    • Implementation & Integration
    • Support & Maintenance


  • Branding & Marketing Management
  • Supply Chain Analytics
  • Competition Benchmarking
  • Governance, Risk & Compliance
  • Customer Analytics
  • Others

Enterprise Size:

  • Small & Medium Enterprises (SMEs)
  • Large Enterprises


  • BFSI
  • Retail & CPG
  • IT & Telecom
  • Media & Entertainment
  • Education
  • Healthcare and Life Sciences

Get a trial Copy

Mon, 17 Oct 2022 01:07:00 -0500 Ankush Nikam en-US text/html
Killexams : With 9.7% CAGR, Cyber Security Managed Services Market Size to Reach USD 25.77 Billion [2022-2029]

Pune, India, Oct. 17, 2022 (GLOBE NEWSWIRE) -- The global cyber security managed services market size was valued at USD 12.52 billion in 2021. The market is projected to grow from USD 13.52 billion in 2022 to USD 25.77 billion by 2029, exhibiting a CAGR of 9.7% during the forecast period.

This information is provided by Fortune Business Insights, in its report, titled, "Cyber Security Managed Services Market Share, 2022-2029."

Managed Services Related to Investment Security are Growing amid COVID-19 Pandemic that Boosted Market Expansion

Individuals and companies are required under COVID-19 norms to accept remote working. Virtual Private Network (VPN) servers have become essential for businesses as more workers choose to work from home. Attributed to this, cybercriminals across the world are surely profiting from this issue. Spam, ransomware, and phishing assaults have increased as a result of hackers using this crisis as a pretext to impersonate brands and trick employees.

Request trial Copy of the Report:

Report Coverage Details
Forecast Period 2022-2029
Forecast Period 2022 to 2029 CAGR 9.7%
2029 Value Projection USD 25.77 Billion
Base Year 2021
Market Size in 2021 USD 12.52 Billion
Historical Data for 2018-2020
No. of Pages 150


Increasing Demand for Security Systems and Public Safety will Drive Cyber Security Managed Services Market Growth

By service, the market is segmented into Managed Detection and Response (MDR), incident management, managed vulnerability, identity and access solutions, and others (endpoint management, data encryption).

Rising Security Concern in Large Enterprises is Driving Market

Based on enterprise size, the market is segmented into SMEs and large enterprise.
Among these, large enterprise segment held the major market share in 2021, and SMEs are expected to grow at the highest CAGR during the 2022-2029.

Increasing Demand for Digital Privacy Systems and Robust Security across IT & Telecom to Drive Market Forward

By industry, the market is segmented into BFSI, IT & telecom, retail, healthcare, government, manufacturing, travel & transportation, energy & utilities, and others.
Among these, healthcare segment held the major market share in 2021. Across the healthcare industry, internet security solutions aid in providing data protection for customer healthcare records. 

Geographically, the market is segmented across five major regions, North America, Europe, Asia Pacific, the Middle East & Africa, and South America.

Report Coverage:

The report offers valuable insights obtained by thorough study done by our researchers. An extensive research was conducted to provide the estimated size of the market. The data used to project the shares for multiple segments at the country, regional, and global levels is obtained from in-depth interviews with numerous stakeholders. Furthermore, we have gained access to several global and regional paid databases to deliver precise information to make business investment decisions easy.

Ask For Customization:

Drivers and Restraints:

Trend of Zero Strategy Implementation to Surge Development of Global Market

Due to pandemic interruptions, there have been major adjustments in cyber security managed services during the last few years. Zero Trust is becoming a more popular and successful cybersecurity strategy for companies throughout the world. Based on all available information and signals, this security model assumes a breach and assesses the security of endpoints, networks, identities, and other resources. To achieve least privileged access and lessen cyber dangers, contextual real-time policy enforcement is necessary. Rapid attack prevention, correction, and detection are made possible by evolving technology leveraging massive datasets and behavior analytics.

Regional Insights:

North America to Take the Lead Supported by Machine Learning Adoption

In 2021, North America held the largest cyber security managed services market share. The market in the region is anticipated to be driven by the quick development of managed security services with the implementation of machine learning and artificial intelligence capabilities.

Asia Pacific is projected to rise with a spectacular CAGR during the forecast period owing to developing governments, presence of key players, and foreign investor investments in numerous blockchain, smart city, and other projects.

The European market displayed decent growth backed by the rising usage of software-defined IT infrastructure and partnerships, collaboration, and service upgrades.

Competitive Landscape:

Key Players Declare Innovative Product Launches to Sustain Market Growth

The chief cyber security managed services players utilize a variety of tactics to reinforce their position as the industry's top businesses. One such critical tactic is the acquisition of businesses to surge brand value among customers. Periodically launching novel products after conducting a thorough analysis of the market and its target audience is another important strategy.

Key Industry Development:

February 2022: IBM unveiled a cybersecurity hub in Bengaluru, its second center globally, for Asia Pacific clients. This hub provides IBM-managed security services, research, India software labs, consulting, and admission to the company's incident response team as well as a garage.

Companies Mentioned in the Cyber Security Managed Services Market Report:

  • BDO Global (Belgium)
  • Secureworks, Inc. (U.S.)
  • Atos SE (France)
  • Wipro (India)
  • IBM Corporation (U.S.)
  • Tata Consultancy Services Limited (India)
  • AT&T Intellectual Property (U.S.)
  • Trustwave Holdings, Inc. (U.S.)
  • Thrive (U.S.)
  • SecurityHQ (India)
  • ECI (U.S.)

Quick Buy - Cyber Security Managed Services Market Research Report:

Major Points in TOC:

  • Introduction
    • Definition, By Segment
    • Research Methodology/Approach
    • Data Sources
  • Executive Summary
  • Market Dynamics
    • Macro and Micro Economic Indicators
    • Drivers, Restraints, Opportunities and Trends
    • Impact of COVID-19
      • Short-term Impact
      • Long-term Impact
  • Competition Landscape
    • Business Strategies Adopted by Key Players
    • Consolidated SWOT Analysis of Key Players
    • Global Cyber Security Managed Services Key Players Market Share Insights and Analysis, 2021      
  • Global Cyber Security Managed Services Market Size Estimates and Forecasts, By Segments, 2018-2029
    • Key Findings
    • By Services (USD)
      • Managed Detection and Response (MDR)
      • Incident Management
      • Managed Vulnerability
      •  Identity and Access Solution
      • Others (End Point Management, Data Encryption, Etc.)
    • By Enterprise Size (USD)
    • By Industry (USD)
      • BFSI
      • IT & Telecom
      • Retail
      • Healthcare
      • Government
      • Manufacturing
      • Travel & Transportation
      • Energy and Utilities
      • Others (Education, Media & Entertainment, Etc.)
    • By Region (USD)
      • North America
      • South America
      • Europe
      • Asia Pacific
      • Middle East & Africa
  • North America Cyber Security Managed Services Market Size Estimates and Forecasts, By Segments, 2018-2029
    • Key Findings
    • By Services (USD)
      • Managed Detection and Response (MDR)
      • Incident Management
      • Managed Vulnerability
      •  Identity and Access Solution
      • Others (End Point Management, Data Encryption, Etc.)
    • By Enterprise Size (USD)
    • By Industry (USD)
      • BFSI
      • IT & Telecom
      • Retail
      • Healthcare
      • Government
      • Manufacturing
      • Travel & Transportation
      • Energy and Utilities
      • Others (Education, Media & Entertainment, Etc.)
    • By Country (USD)
      • United States
      • Canada
      • Mexico
  • South America Cyber Security Managed Services Market Size Estimates and Forecasts, By Segments, 2018-2029

TOC Continued…!

About Us:

Fortune Business Insights™ offers expert corporate analysis and accurate data, helping organizations of all sizes make timely decisions. We tailor innovative solutions for our clients, assisting them to address challenges distinct to their businesses. Our goal is to empower our clients with holistic market intelligence, giving a granular overview of the market they are operating in.

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Sun, 16 Oct 2022 21:53:00 -0500 text/html
Killexams : Breakwater Revolutionizes Data Privacy Market with an Efficient, Cost-Effective Solution for Companies Who Need to Manage Unstructured Data

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

Breakwater Revolutionizes Data Privacy Market with an Efficient, Cost-Effective Solution for Companies Who Need to Manage Unstructured Data

AUSTIN, Texas, Oct. 12, 2022

New Breakwater Data Privacy as a Service solution combines flexible deployment options with implementation and operation methodologies designed to easily and rapidly launch a foundational privacy program for unstructured data.

AUSTIN, Texas, Oct. 12, 2022 /PRNewswire/ -- Breakwater, a leader in data risk management solutions, today announced the launch of an efficient, cost-effective privacy solution for companies that need to manage unstructured data stored either in cloud or on-premises systems. Many organizations continue to struggle with the myriad of privacy obligations as existing options are costly and complex. To meet the needs of customers, Breakwater has brought to market a solution that combines foundational capabilities with the "how to" knowledge to help companies move beyond unactionable policies.

Breakwater Data Privacy as a Service (DPaaS) allows companies to discover, analyze, and protect data from privacy risks with a solution that combines a modern data discovery and management platform, an implementation methodology designed by Breakwater's privacy experts, and operational processes designed by Breakwater's managed services team. Standard operational models are supported, from self-service to managed assistance to full operational management by Breakwater or one of its managed services partners (MSPs).

The solution helps customers understand and prioritize areas of privacy risk, allowing a more efficient approach to remediation efforts. Automation for the solution is provided by Breakwater Privacy, an application built on the Breakwater Governance Cloud platform. Breakwater Privacy enables customers to identify high risk personal and sensitive information and remediate data privacy concerns by connecting to multiple unstructured data sources and leveraging artificial intelligence (AI) to trial and segment data targeting hot spots. Problematic data can be grouped, and policy-driven actions like Quarantine, Delete, and Append Name can be applied. Encryption will soon be available. These capabilities also benefit proactive cybersecurity by protecting or removing files containing sensitive information that may be compromised during a cyber incident.

"Data volumes continue to expand at an unsustainable rate," said Ryan O'Leary, Research Director, Privacy and Legal Technology, IDC. "Expanding data volumes coupled with strong data privacy regimes popping up around the globe require organizations to focus on their data privacy compliance activities. Enterprises need to carry out their privacy compliance activities and still run their business. Enterprises will need to partner with technology and data privacy experts like Breakwater Solutions to augment their internal processes to be successful in the new data privacy conscious business climate."

A more efficient approach to privacy

Breakwater Privacy is designed to simplify the implementation and ongoing operation of the fundamental data protection functions for unstructured data within an organization. Breakwater Privacy supports four foundational aspects of a privacy program:

  • Privacy Risk Assessment
  • Data Profiling and Classification
  • Risk Mitigation and Data Minimization
  • Data Migration and Localization

Key capabilities that make Breakwater Privacy different include:

Playbooks that accelerate implementation and optimize operation

Breakwater provides best practices designed by experienced industry professionals in privacy, information governance, and cyber security to help customers move from planning to operation. Breakwater's privacy playbook helps align requirements and processes, enabling technology to drive automation. Combined with a privacy runbook that provides detailed operational instructions, customers can use this expert knowledge to rapidly deploy and operate Breakwater-delivered solutions either by themselves, in partnership with their managed service providers (MSPs), or with assistance directly from Breakwater.

A new approach to analyzing data using AI segmentation and sampling

Breakwater Privacy changes the approach to data privacy by providing a practical methodology for identifying and prioritizing data stores with high volumes of sensitive data and personally identifiable information (PII) through AI segmentation and sampling. AI segmentation is the process of creating the equivalent of a fingerprint of files that contain sensitive personal data and PII. Sampling is the process of evaluating a select number of files out of an entire corpus and extrapolating the analysis to the larger data set with a level of confidence. Combined, these techniques provide the fastest method to profile and reduce risk in large volumes of data.

Out-of-the-box categorizations

Breakwater provides a set of out-of-the-box categorizations to reduce the time and complexity of initiating a privacy program. These categorizations prioritize the discovery elements of sensitive information that are the riskiest. The categories cover Personal, Financial, Health, Employment & Biometric Data and can be utilized to help comply with multiple regulations, including CCPA, GDPR, LGPD, HIPPA, and PCI.

Flexible technology designed to make your IT experts say yes.

Breakwater Privacy runs on the Breakwater Governance Cloud, which can be implemented via all modern technology deployment models - multi-tenant SaaS, single-tenant public or private cloud, or on-premises. The platform scales to large enterprises through the deployment of decentralized processing nodes. Additionally, organizations can deploy the multi-tenant option with instances within individual regions in compliance with data localization requirements.

Designed by industry veterans

This new solution is driven by the former IBM information governance team, led by James Schellhase, with private equity funding from JLL Partners. Breakwater's product team are experts in unstructured data management within the industry, having delivered solutions for information governance, privacy, compliance, and eDiscovery. This release marks their third enterprise-class unstructured data platform.

"Privacy compliance is constantly evolving with new regulations being discussed, debated, codified, and enacted. Therefore, as the legal and regulatory community strives to understand the impact of these new regulations, the regulators expect review, remediation, and ongoing reasonable efforts to become compliant," said James Schellhase, Chief Executive Officer, Breakwater. "Our approach is to bridge the gap between regulations, technology, and the limited institutional knowledge and expertise most companies are able to attract to help our clients begin their journey to privacy compliance at a foundational level. With Breakwater Data Privacy as a Service and the knowledge of our consulting team, our clients can protect themselves and their customers by identifying and addressing the highest areas of risk."

About Breakwater
Breakwater helps enterprises mitigate risk and gain insight from sprawling information by combining technology automation and human expertise. We empower governance, legal, and risk professionals to locate, access, analyze, and manage information by making data transparent and actionable. Our solutions are comprised of expert consulting, AI-infused technology, and ongoing managed services, all of which directly address the myriad challenges within information governance, disputes and investigations, regulatory compliance, privacy, and cybersecurity. Learn more at

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SOURCE Breakwater Solutions, LLC


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Wed, 12 Oct 2022 01:00:00 -0500 en-US text/html
Killexams : AI in Manufacturing Market Size to Reach $17,925.50 Mn at a CAGR of 51.5% | Vantage Market Research

WASHINGTON, Oct. 10, 2022 (GLOBE NEWSWIRE) -- Global Artificial Intelligence (AI) in Manufacturing Market was valued at USD 1,482.50 Million in 2021 and is projected to surpass the valuation of USD 17,925.50 Million by 2028 at a CAGR of 51.5% during the forecast period 2022–2028. The research on AI in the manufacturing market includes a comprehensive analysis of the global market scope, as well as regional and country-level market size, market segmentation, growth, share, competition Landscape, sales analysis, the effect of domestic and global market players, value chain optimization, trade regulations, current developments, opportunities analysis, strategic market growth analysis, product launches, and technical advancements.

The material that is shot, scattered, dropped, or detonated from any weapon, such as bombs or rockets, and more specifically, the shot, shrapnel, bullets, or shells that are fired by firearms is referred to as AI in Manufacturing. AI in Manufacturing can be thought of as both a throwaway weapon and the components of other weapons responsible for producing the effect on a target. AI in manufacturing can take on a wide variety of shapes and sizes, and it is frequently developed with the sole purpose of functioning within particular sorts of weaponry.

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Artificial Intelligence is the branch of computer science that deals with making smart machines that requires human intelligence. Artificial Intelligence is believe to be the gamechanger in the industry of manufacturing. The rising adoption of Industrial 4.0 is likely to drive the growth of the market in the upcoming years. In manufacturing plants, the information obtained from various sensors, software's, IOT driven system may become complex for human to analyse, in such situation use of Artificial Intelligence is the most efficient solution. In addition to Artificial Intelligence, with the help of Machine learning and pattern recognition, the manufacturing sector can transform completely. The use of AI in Manufacturing Market plant allows the user to analyse and predict consumer behaviour, predict preventive maintenance to prevent unwanted shutdown, detect abnormalities in production process and much more. AI also facilitates the use of real time information which could improves the decision-making time boosting the growth of organization. Moreover, increasing volume of data gathered through various devices, coupled with the widespread availability of high-speed broadband networks and the upcoming implementation of 5G technologies will further contribute to the global AI in Manufacturing Market in the coming years. Whereas, the lack of skilled expertise and infrastructure and high operation along with lack of awareness are some of the factor that are about to hamper the growth of AI in Manufacturing Market.

Key Insights & Findings from the Report:

  • According to our primary respondents' research, the AI in Manufacturing market is predicted to grow at a CAGR of roughly 51.5% during the forecast period.
  • The AI in Manufacturing market was estimated to be worth roughly USD 1,482.50 Million in 2021 and is expected to reach USD 17,925.50 Million by 2028; based on primary research.
  • On the basis of region, Asia-Pacific is projected to dominate the worldwide AI in Manufacturing market.

List of Prominent Players in the Global AI in Manufacturing Market:

  • NVIDIA Corporation (US)
  • IBM Corporation (US)
  • Alphabet Inc. (Google) (US)
  • Microsoft Corporation (US)
  • Intel Corporation (US)
  • Siemens AG (Germany)
  • General Electric Company (US)
  • General Vision Inc. (US)
  • Progress Software Corporation (US)
  • Micron Technology Inc. (US)
  • Mitsubishi Electric Corporation (Japan)
  • Sight Machine (US)
  • Cisco Systems Inc. (US)
  • SAP SE (Germany)
  • Rockwell Automation Inc. (US)
  • AIBrain Inc. (US)
  • Vicarious Inc. (US)
  • Oracle Corporation (US)
  • Amazon Web Services (US)
  • Spark Cognition Inc. (US)
  • Rethink Robotics (Germany)
  • UBTECH Robotics Corp. (China)
  • Aquant Inc. (Israel)
  • Bright Machines (US)
  • Flutura Decision Sciences & Analytics (India)

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The AI in Manufacturing Market is segmented as below:

  • Offering (Hardware, Software, Services).
  • Technology (Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision).
  • Application (Predictive Maintenance and Machinery Inspection, Material Movement, Production Planning, Field Services, Quality Control, Cybersecurity, Industrial Robots, Reclamation).
  • Industry (Automobile, Energy and Power, Pharmaceuticals, Heavy Metals and Machine Manufacturing, Semiconductors and Electronics, Food & Beverages, Others).

Market Dynamics:

Driver- Increase in adoption in AI technology for production optimization

Industries like automobiles, chemical, electronics, food among others are witnessing the need for production optimization due to competitive environment. Artificial intelligence and Machine Learning the two powerful tools to minimize the consumption of resources in every industrial process and maximize the output by optimizing the power consumption. AI and ML are build a statistical model using available data from various sensors, material used in manufacturing and various software's. Based on this data it predicts the accurate parameter for final product resulting in saving extra material and additional resources in the production process. This enables the business to make the production cost effective.

Driver-Implementation of Industrial 4.0

The influence of industrial 4.0 on the manufacturing sector is tremendous. With 4.0 the industries are getting smarter by adoption of smart sensors, interconnected systems, and others. But due to this a large amount of data is exchanged among the machines. To handle such large amount of data, Artificial intelligence is the best choice as it facilitates intelligent manufacturing. Intelligent manufacturing uses AI based data driven model that that takes manufacturing decision, prediction and real time optimization in manufacturing process. Hence, driving the growth of the AI in Manufacturing Market.


The implementation of AI requires skilled labour who can handle the entire process right from start to end. The concerned person should have in depth knowledge about AI, its behaviour, implementation and limitation. Thus, lack of skill and knowledge whether AI can handle the entire process or not is what hampering the growth of AI.

A potential barrier to adoption of AI technology is the manufacturer lack of trust in its capabilities. People without relevant education background often struggle to understand the working model of technology and do not have full confidence in its working.

Browse AI in Manufacturing Market Reports @

Regional Trends:

Asia Pacific is estimated to be the largest shareholder for the Global AI in Manufacturing Market due to the presence of large number of manufacturing companies in China, India, Japan and South Korea and their rising focus on digitalization and technological advancement. Also, the government of India, China, Japan and Singapore are investing in technologies like AI and boosting its use in manufacturing sector and for industries 4.0. China's implementation of AI is very high. The initiative of Indian government like Make in India is motivating the manufacturing sector and startup's to use advanced technology like AI. The government of Singapore is inviting private firm's investment to test AI functionality for the country.

Europe is estimated to be the next biggest shareholder after India, because of countries like UK which are making a huge investment in R&D of advanced technologies like AI. Also, the latest guidelines of government of Italy for the public about the National Strategy in Artificial Intelligence is likely to boost the use of AI in the region. North America, on the other hand, will witness significant growth owing to increasing investment in R&D activities and a growing number of startup's for AI technology.

Recent Development:

  • February 2022, IBM Corporation announced the launch of the IBM Sustainability Accelerator, a global pro bono social impact program that applies IBM technologies, such artificial intelligence, and an ecosystem of experts to enhance and scale non-profit and government organization operations, focused on populations vulnerable to environmental threats including climate change, extreme weather, and pollution.
  • March 2020, Siemens collaborated with NEC to provide manufacturing industries solutions and AI monitoring to accelerate digitalization
  • July 2019, Microsoft partnered and invested $1billion in company named OpenAI. OpenAI enhance Azure platform and build next gen application. Azure will thus be working on running AI technologies.

The report on the Global AI in Manufacturing Market highlights:

  • Assessment of the market
  • Premium Insights
  • Competitive Landscape
  • COVID Impact Analysis
  • Historic Data, Estimates, and Forecast
  • Company Profiles
  • Global and Regional Dynamics

Key Questions Answered in The Report:

  • What is AI in Manufacturing?
  • How big is the AI in Manufacturing market?
  • What is AI in Manufacturing product use for?
  • Who are the key players in the AI in Manufacturing market?
  • What is the scope of growth in the AI in Manufacturing market?
  • What are the key trends in the AI in Manufacturing market report?
  • What is the core strategy for growth in the AI in Manufacturing market?
  • Which is base year calculated in the AI in Manufacturing market report?
  • What are the risks involved in investing in the AI in Manufacturing market?
  • What are the main opportunities for growth in the AI in Manufacturing market?
  • What are the core strategies of key players in the AI in Manufacturing market?

This market titled "Global AI in Manufacturing Market" will cover exclusive information in terms of Geographic Segmentation, Forecast, Regional Analysis, Key Market Trends, and various others as mentioned below:

Parameter Details
Market Size in 2021 USD 1,482.50 Million
Revenue Forecast by 2028 USD 17,925.50 Million
CAGR 51.5% From 2022 – 2028
Base Year 2021
Forecast Years 2022-2028
Segments Covered • Offering

  ° Hardware

  ° Software

  ° Services

• Technology

  ° Machine Learning

  ° Natural Language Processing

  ° Context-aware Computing

  ° Computer Vision

• Application

  ° Predictive Maintenance and Machinery Inspection

  ° Material Movement

  ° Production Planning

  ° Field Services

  ° Quality Control

  ° Cybersecurity

  ° Industrial Robots

  ° Reclamation

• Industry

  ° Automobile

  ° Energy and Power

  ° Pharmaceuticals

  ° Heavy Metals and Machine Manufacturing

  ° Semiconductors and Electronics

  ° Food & Beverages

  ° Others

Region & Counties Covered • North America

  ° U.S.

  ° Canada

  ° Mexico

• Europe

  ° U.K

  ° France

  ° Germany

  ° Italy

  ° Spain

  ° Rest Of Europe

• Asia Pacific

  ° China

  ° Japan

  ° India

  ° South Korea

  ° South East Asia

  ° Rest Of Asia Pacific

• Latin America

  ° Brazil

  ° Argentina

  ° Rest Of Latin America

• Middle East & Africa

  ° GCC Countries

  ° South Africa

  ° Rest Of Middle East & Africa

Companies Covered • NVIDIA Corporation (US)

• IBM Corporation (US)

• Alphabet Inc. (Google) (US)

• Microsoft Corporation (US)

• Intel Corporation (US)

• Siemens AG (Germany)

• General Electric Company (US)

• General Vision Inc. (US)

• Progress Software Corporation (US)

• Micron Technology Inc.(US)

• Mitsubishi Electric Corporation (Japan)

• Sight Machine (US)

• Cisco Systems Inc. (US)

• SAP SE (Germany)

• Rockwell Automation Inc. (US)

• AI Brain Inc. (US)

• Vicarious Inc. (US)

• Oracle Corporation (US)

• Amazon Web Services (US)

• Spark Cognition Inc. (US)

• Rethink Robotics (Germany)

• UBTECH Robotics Corp. (China)

• Aquant Inc. (Israel)

• Bright Machines (US)

• and Flutura Decision Sciences & Analytics (India).

Report Coverage Market growth drivers, restraints, opportunities, Porter's five forces analysis, PEST analysis, value chain analysis, regulatory landscape, technology landscape, patent analysis, market attractiveness analysis by segments and North America, company market share analysis, and COVID-19 impact analysis

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