Survey: The 2024 State of Unstructured Data Management
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Welcome to the latest edition of the Komprise Intelligent Data Management newsletter! We cover new ways for IT managers to be more productive managing enterprise data and storage to dealing with ever-changing compliance issues, working with departments on data strategies and understanding the new requirements for data management and AI. Learn more about Komprise, a SaaS solution for unstructured data management and mobility, and follow us on LinkedIn.??
This month’s newsletter covers the Komprise 2024 State of Unstructured Data Management, our fourth-annual survey of enterprise trends in data growth, storage spend, AI plans, data management challenges and priorities, and IT skills.? This report summarizes responses of 300 global enterprise IT leaders (director and above) at enterprises with more than 1,000 employees in the United States. The survey was conducted by a third party in June 2024.??
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Highlights of the Survey:?
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Download the full report here.?
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Executive Summary: AI on a Budget?
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Across the globe, AI mania is reaching epic proportions. Investors spent $27.1 billion on AI startups in the United States alone from April to June of this year, accounting for nearly half of all startup funding in the country during that period, according to PitchBook. Yet when it comes to implementing these technologies, it’s still early days in the enterprise.?
Most (70%) organizations are still experimenting with these new technologies as “preparing for AI” remains a top data storage and data management priority for IT leaders. Yet cost optimization is an even higher priority this year and they are trying to fit AI into existing IT budgets. Only 30% say they will increase their IT budgets to support AI projects.?
At this stage in the AI game, IT has not yet enforced much restriction on data, users or tools.? Enterprises are instead focused on building out the proper infrastructure and technology stack for AI by upgrading data storage and data management technologies. Another key trend is the need to improve security and governance across GenAI and unstructured data management and more broadly by filling security skills gaps in the IT workforce, our research shows.?
As the startup community and established technology vendors alike rush to launch new products and capabilities for AI, enterprise IT teams are still laying the technical foundation and determining the necessary economic strategies to get started. This year’s survey shows that, when it comes to AI, it all starts with the data and how it is managed, mobilized, protected and prepared for new uses.?
Soundbites from our COO Krishna Subramanian?
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“We thought AI would rank higher than cost optimization, but cost optimization actually ranked the highest, and I think it's because most of the customers we talk to are still trying to figure out AI. They're probably exploring AI a little bit, but they're more concerned about preparing their data for AI, and 70% of them have not budgeted any funds for it. So, they have to fund the AI projects by just squeezing it out of elsewhere. If they want to do an AI project, they're probably going to say, let's be more efficient on storage, or let's be more efficient on compute, and we're going to take those dollars, and we're going to use that for AI.”?
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“As in 2023, moving data without disruption to users and applications is the top technical challenge.? What commonly happens when migrating or archiving data to new storage is that users can’t find their data later: it’s no longer in the same file directory location so they must put in a support ticket for IT. Also, applications can break if they can’t find data that has been moved. These issues are caused by the proprietary methods (such as stubs) that some storage and data management technologies use to move data.???
Another top technical challenge is using AI to classify and segment data. Data classification, which involves identifying and labelling unstructured data, helps people search across petabyte-scale, distributed environments for the files they need or to identify security risks from improperly managed sensitive data. AI-enhanced data classification is a new, highly efficient method, but best practices are still emerging here.??
Prepping for AI is the top business challenge for unstructured data management. There is a lot to figure out in this area from enriching metadata to add structure to the data so it is more usable to efficiently moving data to AI tools, to the whole gamut of security and privacy issues that arise from using GenAI tools in the workplace.”?
Data on the Move?interview with Krishna Subramanian
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Last Words…?
Managing unstructured data today has become more complex all the time. IT leaders not only need to ensure fast, secure access to data for employees but with better cost economics, no disruption when moving it to new storage, meet governance and compliance requirements and prepare this data for AI. We'll be covering the trends as they develop right here!
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