Data Management, Analytics & AI

  • Commvault’s TrAIlblazing Shift

    I recently attended Commvault’s Shift event on November 8 in New York City, along with over 200 customers and partners. I am not easily impressed; it comes with the territory of being an industry analyst. Not this time. The company organized an event that marks another strategic turning point for Commvault. This time, it’s about AI. As I wrote in 2020 and the year before, this is no longer the legacy company of a few years ago. It is intent on leapfrogging others in the market—again. Competitors should take close notice.

    Credit: Photo by Christophe Bertrand

    A few years ago, Commvault redefined itself under the leadership of its then-new (and current) CEO, Sanjay Mirchandani, by making two critical moves: the acquisition of Hedvig and the creation of Commvault Cloud (previously known as Metallic). These significant strategic investments were critical to meet market requirements and competitive pressures at the time and directly positioned the company for today and for what it will be next.

    The strategic shift (pun intended) Commvault is operating is the culmination of a multifaceted technology optimization strategy through operational automation, unification, and efficiency at the platform level and a focus on data resilience at scale. These two key areas of operations and resilience were critical in building and evolving the Commvault Cloud offering while preserving the traditional installed base of on-premises and hybrid customers. The company now claims 4,000 customers for its as-a-service offering. That’s an impressive number.

    This is happening at a critical time in a market that has shifted from traditional disaster recovery to cyber-recovery or cyber-resilience, a fact that ESG recently researched and confirmed.1 Ransomware fundamentally affects business processes and operations, with significant compliance and financial exposure ramifications. The devastating impacts of repeated and often successful ransomware cyber-attacks have become the new normal, making ransomware an existential threat for many organizations. In our recent research, most respondents recognized that ransomware supersedes all other potential threats. Unfortunately, most are not well prepared to deal with it. Few organizations can successfully restore all of their data. 

    The other key trend affecting the data-protection space and beyond is the need to simplify and optimize processes and operations at scale. Many IT teams are trying to keep pace with data growth, and our research shows that they also struggle to protect mission-critical applications and deliver on key recovery objectives. Many IT and cloud operations professionals tasked with backup and recovery responsibilities drown in complexity, multiple tools, and inconsistent processes. Combine this with ransomware and you have a perfect storm. This is reflected in extended RPOs and RTOs and heightened business-level risk.

    Disaster recovery is crucial to business continuity, especially regarding application and data recovery. Testing is a critical best practice that helps identify potential issues with people, processes, and technology and enables corrective measures to be taken. Regular testing is essential for gauging one’s ability to recover from a disaster. However, many organizations find it too complex and expensive to conduct frequent testing. This can lead to extended intervals between tests, which may cause critical interdependencies between infrastructure and security teams to be overlooked. This is particularly concerning in ransomware attacks, where the need for effective collaboration between teams is paramount. Cost and the lack of skill sets are also significant factors that hinder frequent testing. 

    Recognizing this fundamental market change, Commvault has made additional strategic platform investments to bring together data protection, security (including SIEM/SOAR ecosystem integrations), intelligence, and recovery with machine learning and AI operationalizing the most complex and error-prone tasks.    

    On the ransomware front, the platform can help improve recoverability with what the company calls a “cleanroom recovery service,” allowing users to test and detect threats without impacting production. In partnership with Microsoft Azure, the platform uses AI to verify “clean” recovery points and provides a fully ready environment to recover. This is key because hardware microcode or operating systems that make up infrastructure can also be affected by cyber-attacks. So not only does one need a clean recovery point, but one also needs a clean environment to restart.

    A few years ago, Commvault made some crucial architectural decisions that are beneficial because they now clearly help differentiate the company. For instance, separating the control plane from the data plane and the storage plane is now paying off since it allows for an any-to-any set of permutations for moving data around for backup and recovery, whether on-premises or in the cloud. Today, most enterprises operate in a hybrid and multi-cloud environment. 

    Combining testing and recovery capabilities with ecosystem partnerships and integrations, the company is positioning itself as a critical player in the security supply chain without losing its focus on what it does best: data resilience and recoverability. Cloud burst capabilities help address cost at scale by only using compute for a controlled time at a fraction of the cost of a hardware-based approach. This removes the last significant objection to frequent cyber-resilience testing or recovery testing.

    Commvault recognizes that it is not a security company but a data-resilience platform company, one that is part of an ecosystem in which security technology players provide part of the broader solution.

    Over the past few months, I’ve noticed a company that’s less timid and more assertive. They are not afraid to take on their competitors and are doing so effectively with clear and precise messaging. The marketing team has executed its strategy well, and I believe that this same team will be the driving force behind the success of recent announcements, which will go beyond just the technological aspect.

    1. Enterprise Strategy Group Research Report, The Long Road Ahead to Ransomware Preparedness, 2023 ↩︎
  • Discover what’s trending on our network to engage IT buyers in market now and improve marketing and sales effectiveness. This report covers trending areas of interest across 240+ IT markets over the last 6 months (April 2023 – September 2023) in five (5) regions across the TechTarget & BrightTALK network: WW, NA, EMEA, APAC, LATAM.

    In this report you will find:


    • The top 20 broad technology markets driving the most activity in the past 6 months. Activity data can help show where audience research is growing or declining and therefore help reinforce which markets are on the rise or declining.


    • The top 25 granular topics growing the most across the TechTarget and BrightTALK network in the last 6 months. This gives insight into the content areas that are on the rise right now to leverage in your conversations.

    Already an Enterprise Strategy Group client? Log in to read the full report.
    If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us.
  • As AI continues its meteoric rise into business and IT environments, organizations are rapidly assembling or accelerating strategies to support AI technologies across every applicable area. While many organizations are consistent in their efforts to build AI strategies, the components and direction of those strategies often vary. TechTarget’s Enterprise Strategy Group recently surveyed data and IT professionals responsible for the infrastructure supporting AI initiatives at their organization to gain insights into these trends.

    To learn more about these trends, download the free infographic, Navigating the Evolving AI Infrastructure Landscape.

  • As AI continues its meteoric rise into business and IT environments, organizations are rapidly assembling or accelerating strategies to support AI technologies across every applicable area. Unlike niche technologies that impact only certain processes or personnel, AI has wide-ranging potential to transform entire businesses, IT environments, and associated teams. In turn, AI strategies must be multi-pronged efforts that properly align business objectives with AI initiatives and expectations, which requires thorough participation from stakeholders across the organization. The underlying infrastructure and other supportive elements must be fully capable of supporting that tandem strategy.

    While many organizations are consistent in their efforts to build AI strategies, the components and direction of those strategies often vary. To assess the evolving AI landscape and the infrastructure that supports it, TechTarget’s Enterprise Strategy Group surveyed 375 data and IT professionals in North America (US and Canada) responsible for strategizing, evaluating, purchasing, and/or managing infrastructure specifically supporting AI initiatives for their organization. This study sought to answer the following questions:

    • What are the primary business objectives for implementing AI? How long does it take for organizations to start seeing value from AI initiatives?
    • What are the top challenges organizations encounter when implementing AI?
    • What individuals or teams influence decision making related to infrastructure used to support AI initiatives? Which of these has the most influence on final decisions?
    • How are organizations planning to address skills gaps related to the selection, implementation, and management of infrastructure supporting AI initiatives?
    • In which physical locations do organizations primarily deploy their AI infrastructure? What are the top factors that influence the choice of these locations? Are AI environments mostly centralized, mostly decentralized, or an even mix of both?
    • What capabilities of AI infrastructure are most important?
    • Are organizations using internal resources, third-party resources, or both to manage their AI infrastructure?
    • How important is sustainability and environmental responsibility when selecting AI infrastructure? How important is a vendor’s stance on these factors when making purchase decisions for AI infrastructure?
    • What types of data do organizations use to build and train AI models and algorithms? What steps do organizations take to ensure accuracy in the data used for building and training these models?
    • How do organizations handle the movement of the large amounts of data required to support AI initiatives? What challenges are involved with this process?
    • How are organizations using synthetic and third-party data to support AI model training?
    • How are organizations using generative AI (GenAI)? What challenges are they encountering?
    • To what extent are developers leveraging AI infrastructure resources? How do developers access these resources?
    • How do organizations measure the success and effectiveness of AI initiatives?
    • What is AI’s impact on employee productivity, processes, workflows, competitiveness, and other factors?

    Survey participants represented a wide range of industries, including financial, manufacturing, retail/wholesale, and healthcare, among others. For more details, please see the Research Methodology and Respondent Demographics sections of this report.

    Already an Enterprise Strategy Group client? Log in to read the full report.
    If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us.
  • Cloud Data Protection Strategies at a Crossroads

    The broad adoption of public cloud services and containers as sources and repositories of business-critical data puts the onus on data owners to deliver on data protection SLAs for cloud-resident and container-based applications and data. As vendors and the cloud ecosystem evolve and add as-a-service consumption options, end-users are making incorrect comparisons and assumptions, leading to lasting challenges and a market at a crossroads.

    Learn more about these trends with this free infographic.

  • Generative artificial intelligence (GenAI) recently stormed the market and mindshare of decision makers across industries and major geographic markets. Business leaders see a massive opportunity to positively impact operations and customer strategies with GenAI, but its adoption and use across all business units carry a fair share of trepidation.

    Learn more about these trends with the infographic, Beyond the GenAI Hype: Real-world Investments, Use Cases, and Concerns.

  • Cloud Data Protection Strategies at a Crossroads

    Research Objectives

    The broad adoption of public cloud services and containers as sources and repositories of business-critical data puts the onus on data owners to deliver on data protection SLAs for cloud-resident and container-based applications and data. Users are confused about the data protection levels that public cloud and Kubernetes environments deliver and about the changing protection options (DIY in the cloud, cloud-native third-party solutions, hyperscalers’ built-in features, as-a-service, etc.). As vendors and the cloud ecosystem evolve and add as-a-service consumption options, end-users are making incorrect comparisons and assumptions as well as failing to select the key data protection capabilities they need to maximize their cloud technology investments. This confusion leads to lasting challenges, and the market is now at a crossroads.

    To assess the state of cloud-based data protection and the as-a-service market (e.g., in cloud/to the cloud, BaaS, and DRaaS), TechTarget’s Enterprise Strategy Group (ESG) surveyed 397 IT professionals in North America (US and Canada) familiar with and/or responsible for data protection technology decisions for their organization, specifically around data protection and production technologies that may leverage cloud services as part of the solution. This study sought to answer the following questions:

    • How do organizations define backup-as-a-service (BaaS) and disaster recovery-as-a-service (DRaaS)?
    • What is the adoption status of BaaS, DRaaS, and cloud backup/disaster recovery targets?
    • What groups/roles within organizations are involved with the evaluation of and influence the purchase of public cloud-based data protection solutions? Which group/role typically makes the final purchase decision?
    • How many times in the last 12 months have organizations had to recover data from on-premises and/or public cloud environments? What percentage was recovered on average in those cases?
    • What were the reasons for data recovery efforts in the last 12 months?
    • Would organizations consider a public cloud-based data protection solution that includes an on-premises cache or storage for local recovery to improve data recovery SLAs (e.g., RPO)?
    • What approaches currently protect applications/workloads/data in public cloud infrastructure services?
    • What types of data protection technologies are used in these approaches, and which assets are protected?
    • How is critical public cloud-based unstructured data protected, and what are acceptable recovery times?
    • What is the impact on teams of the daily management and maintenance of public cloud data?
    • How many full-time staff are allotted for data protection objectives associated with cloud data?
    • What methods do organizations use to protect data within virtual machines on public cloud infrastructure?
    • What are organizations’ preferred approach to protecting multiple unique public CSP environments?
    • How do organizations estimate the costs of their cloud backups and recoveries for hyperscalers?
    • What approaches do organizations take to ensure cost-efficient data tiering for the data protection storage supporting their public cloud infrastructure-resident applications?
    • Does organizations’ backup software handle the appropriate tiering of data written to object storage?
    • How important is it to have a container backup and recovery management solution that works across multiple disparate public cloud infrastructure services going forward?
    • Do organizations’ container backup schemas integrate with their current data protection environment?

    Survey participants represented a wide range of industries, including financial, manufacturing, retail/wholesale, and healthcare, among others. For more details, please see the Research Methodology and Respondent Demographics sections of this report.

    (more…)

  • Application developers are challenged with efficiently creating innovative solutions while managing time constraints, which can be mitigated by the transformative impacts of generative artificial intelligence (AI) streamlining code generation and accelerating development processes. Organizations have integrated generative AI (GenAI) into their operational setup to accelerate code creation, refine code structures, elevate code quality, and deliver personalized customer experiences. By harnessing GenAI, application developers tackle issues by capitalizing on the technology’s ability to automate tasks, drive creativity, and deliver innovative solutions.

    (more…)

  • The Strategic and Evolving Role of Data Governance

    For organizations on a digital transformation journey, sound data governance practices must play a strategic role. As the amount of data and value of that data to the business continue to increase, so too does the importance of managing its availability, usability, integrity, and security.

    Learn more about these trends with the infographic, The Strategic and Evolving Role of Data Governance.

  • About This Report

    This report covers trending areas of interest across 240+ IT markets over the last 6 months (January 2023 – June 2023) in five (5) regions across the TechTarget & BrightTALK network: WW, NA, EMEA, APAC, LATAM.

    • Top 20 markets driving activity
      • Represents the top 20 broad technology markets driving the most activity in the last 6 months. Activity data can help to show where audience research is growing or declining and therefore help reinforce which markets are hot or declining.
    • 25 topic areas on the rise
      • Shows the top 25 granular topics growing the most across the TechTarget network in the last 6 months. This gives insight into the content areas that are on the rise right now.

    Discover what’s trending on our network, which you can leverage to engage IT buyers in market now and improve marketing and sales effectiveness.

    Already an Enterprise Strategy Group client? Log in to read the full report.
    If you are not yet a Subscription Client but would like to learn more about accessing this report, please contact us.
  • Research Objectives

    • Determine the current market state of generative AI, including adoption and budget strategies.
    • Identify current and planned GenAI use cases and prioritization across organizations.
    • Understand key challenge areas with GenAI and investment requirements to address them.
    • Investigate key areas of application and focus for GenAI technologies, including cybersecurity, application development, analytics, and customer experience. (more…)