Data management is having a moment

While this week has been a bit quieter than last when it comes to technology news, we did have one bombshell drop on Tuesday when Salesforce announced its intent to acquire Informatica for $8 billion. It’s a big chunk of cash for a company born in the 1990s, but Salesforce saw a chance to get an enterprise-scale data management tool in the fold and it didn’t flinch. It’s only cash after all.

Data has taken a central role for the enterprise in the age of generative AI. As we’ve discussed often in this space, good data is key to the success of AI projects and garbage in/garbage out, the notion that if you build applications based on bad data, you will have bad outcomes, still applies. 

What’s more, companies like IBM have been talking about smaller, more focused models lately that take advantage of company-specific data. As IBM CEO Arvind Krishna put it at IBM Think earlier this month, “To win, you are going to need to build special purpose models, that are much smaller, tailored for a particular use case, and that can ingest the enterprise data and then work.”

Perhaps it’s not a coincidence that IBM closed a deal to acquire DataStax this week, a data management company built on the open source Apache Cassandra project. As DataStax CEO Chet Kapoor put it on LinkedIn announcing the deal had closed, “Our mission remains the same -- empowering enterprises and developers to build and scale mission-critical applications.”

A pattern emerges

It’s part of a pattern we are seeing where large companies like IBM and Salesforce are using their wallets to scoop up data management tooling at a time it’s becoming increasingly important to find ways to access that mission-critical data Kapoor referred to, data that’s often trapped in legacy systems. The idea is to take this data in older systems and put it in modern formats that large language models can consume and understand.

Thomas Squeo, chief technology officer at Thoughtworks, a technology consultancy, says his company has been working to help clients unlock legacy data, which he believes is going to be essential for many organizations moving forward. “AI has made data lock-in an existential threat for some enterprises because they're going to be out-competed by new players that are not encumbered by that,” he said. He’s talking about newer companies that were built from the ground up on top of a more modern data stack.

“AI has made data lock-in an existential threat for some enterprises because they're going to be out-competed by new players that are not encumbered by that."

~Thomas Squeo, Thoughtworks CTO

But those organizations dealing with legacy data problems need to think more deeply about, and put more resources into getting their data in order. Perhaps companies like IBM and Salesforce see this as a way to help companies sitting on large legacy data stores to position themselves better for an AI future.

What if they're right?

Jack Gold, principal at J. Gold Associates, certainly sees it that way. Writing about the Salesforce-Informatica deal on LinkedIn, he said, “Even if you believe that legacy data management isn't the future, it will be in place for a very long time, and it's a critical stepping stone to AI.”

If he’s right, Salesforce’s $8 billion bet might pay off handsomely by making it easier for customers to access all that data locked in those older systems. What’s more, pairing Informatica with MuleSoft, a tool built to connect to legacy systems via APIs, fits neatly into Salesforce’s broader agentic vision where Informatica handles the data management, while MuleSoft helps build the connectors the agents rely on to move between systems.

Regardless, it feels like we’ve reached a point where large companies are recognizing that it’s going to be critical for them to help customers get at data wherever it lives, and we could see data management tools increasingly in demand as M&A targets as a result. Perhaps Salesforce and IBM are just ahead of the game.

~Ron

Featured image by Deng Xiang on Unsplash