This blog was adapted from its original version on VMblog.com
We launched our company in 2014 to create a solution for the new category of unstructured data management. While some of the early tenets that we created the company around – regaining control over unstructured data and getting deep visibility into data to make better decisions and maximize cost savings – are still paramount for customers, there is so much more today. Today we see a host of new requirements for AI, self-service, departmental collaboration, cloud migrations and compliance. I’ve put together some predictions for next year in that light here.
Storage Teams Advance User Self-Service
The trends towards IT-as-a-Service coupled with increased interest in AI are causing enterprise storage teams to look for ways to manage data across storage vendors and deliver new and improved data services to business users. Most (85%) of IT leaders in the Komprise 2023 State of Unstructured Data Management say that non-IT users should have a role in managing their own data and 62% already have attained some level of user self-service for unstructured data management. Data storage professionals will need to focus on tighter collaboration with departments, such as through showback reporting, to cut costs by finding and tiering cold data and eliminating unnecessary duplicates. End users should be able to quickly search for the types of files they need and inform IT about their intentions so that IT can set policies for data movement – such as to a cloud AI service.
IT Will Create GenAI Guardrails for Data
The Komprise survey shows that organizations are largely allowing employee use of GenAI and most have outlined some restrictions on data or applications. Yet there are limitations on guardrails due to the early, amorphous nature of the technology and a lack of understanding in how the tools work behind the scenes and what vendors are doing (or not) to protect organizations and their data. It’s hard to fully control employee use, as with shadow IT. The best place to start is to create and enforce a comprehensive data governance framework that manages the Security, Privacy, Lineage, Ownership, and Governance (SPLOG) of data interactions with AI. Read our blog post here.
AI Data Governance Will be Layered
Given the multifarious threats from generative AI, it’s hard to imagine a single AI data governance solution that will fit the bill. Instead, there will be layers of AI security tools, starting at the network layer to prevent the access of blocked data by an AI tool or prevent users from sending corporate data to unauthorized AI services. There would be another level of protection at the data layer which audits which data was moved, where, when and by whom and alerts if PII or sensitive data is being shared. Finally, there could be a security mechanism at the user layer that may warn users when they are engineering prompts with corporate or sensitive data or provides feedback when prompts may be giving away too much corporate context.
Cloud Migrations Will Require Specific Cost Optimization Strategies
Common tactics to avoid cloud waste include leveraging cost savings plans and other pricing promotions offered by the cloud vendors, using commercial spend monitoring tools, deleting duplicate and orphaned data and reducing cloud sprawl through automated discovery and corporate policies. An independent unstructured data management solution informs cloud migrations by giving storage and IT managers a means to view and analyze data assets across all storage and establish automated movement of data to the most cost-effective storage solution for current needs. This avoids data sitting endlessly on high-priced storage when it’s no longer active. Continuous data lifecycle management through automated policies can also ensure that data moves to the optimal location as it ages or its business value changes.
IT Will Seek Unified Storage and Data Metrics
Storage managers do not have a single console to see detailed usage and capacity data on both storage and data assets. This is important now because unstructured data growth has exploded in recent years, creating massive strain on IT budgets and complexity plus increased security and compliance risks. Plus, storage managers are increasingly procuring storage from many different vendors. That’s making it difficult to see trends to save money or manage capacity, performance and security more effectively for end users. Komprise introduced Storage insights this fall to help customers work more effectively and productively. As industry analyst Steve McDowell remarked recently in Forbes: “Storage Insights is unique in the market in providing a holistic view of an enterprise’s unstructured data across cloud boundaries, including data stored on-prem on nearly every storage vendor’s solution. That’s powerful.”
