AI is forcing the data industry to consolidate — but that’s not the whole story

The data industry is about to a drastic transformation.

The market consolidates. And if the deal stream is an indicator in the past two months – with Databricks that buy NEON for $ 1 billion and Salesforce that cloud management company computer science for $ 8 billion – builds the momentum for more.

The acquired companies can vary in size, age and focus area within the data stack, but they all have one thing in common. These companies are purchased in the hope that the acquired technology will be the missing piece that is necessary to get companies to use AI.

This strategy is logical at the surface level.

The success of AI companies and AI applications is determined by access to underlying quality data. Without this there is simply no value – a conviction shared by Enterprise VCs. In a WAN survey in December 2024, Enterprise VCS said that the data quality was a key factor to make AI startups stand out and to succeed. And although some of these companies involved in these deals are not startups, sentiment is still.

Gaurav Dhillon, the former co-founder and CEO of Computer Science, and current chairman and CEO of data integration company Snaplogic, repeated this in a recent interview with WAN.

“There is a complete reset in how data is managed and flowing around the company,” said Dhillon. “If people want to grab the AI ​​imperative, they have to re -do their data platforms in a very large way. And this is where I believe you see all these data acquisitions, because this is the basis to have a good AI strategy.”

But is this strategy to break up companies that are built before a post-chatgpt world, the way to increase the AI ​​acceptance of the Enterprise in today’s fast innovative market? That is unclear. Dhillon also has doubts.

“Nobody was born in AI; that’s only three years old,” said Dhillon, referring to the current Post-Chatgpt AI market. “For a larger company, to offer AI innovations to imagine the company again, in particular the agent company, it needs a lot to make it happen.”

Fragmented data science

The data industry has grown over the past decade into a vast and fragmented web – making it ripe for consolidation. The only thing needed was a catalyst. From 2020 to 2024 alone, according to PitchBook data, more than $ 300 billion was invested in data startups in more than 24,000 deals.

The data industry was not immune for the trends that were seen in other industries such as Saas, where the company of the last decade resulted in numerous startups that were financed by venture capitalists who only awarded a specific area or in some cases were built around a single function.

The current industrial stand of bundling a number of different data management solutions, each with its own specific focus, does not work when you want AI to crawl around your data to find answers or to build applications.

It is logical that larger companies are looking for startups that can connect to and can fill existing holes in their data stack. A perfect example of this trend is Fiveetran’s recent census acquisition in May – what yes, was done in the name of AI.

Fivetran helps companies to relocate their data from different sources in cloud databases. For the first 13 years of his company, it was not allowed to get this data back from the aforementioned databases, which is exactly what Census offers. This means that prior to this acquisition, FiveTran customers had to work with a second company to create an end-to-end solution.

For the sake of clarity, this is not intended to shed shadow on Fivetran. At the time of the deal, George Fraser, the co-founder and CEO of Fiveetran, told WAN that although moving data in and from these warehouses seems two sides of the same coin, it is not that simple; The company even tried an internal solution to this problem.

“Technically, if you look at the code underneath [these] Services, they are actually quite different, “Fraser said at the time.” You have to solve a fairly different series of problems to do this. ‘

This situation helps illustrate how the data market has been transformed in recent decade. For Sanjeev Mohan, a former Gartner analyst who now runs Sanjmo, his own consultancy firm for data trend, these types of scenarios are a large driver of the current Gulf of Consolidation.

“This consolidation is powered by customers who are tired of a multitude of products that are incompatible,” said Mohan. “We live in a very interesting world where there are many different data storage solutions, you can do open source, they can go to Kafka, but the only area we have failed is Metadata. Dozens of these products are recorded of a metadata, but to do their work, it is an overlap.”

Good for startups

The wider market also plays a role here, Mohan said. Data startups are struggling to attract capital, Mohan said, and an exit is better than for debts to end or load. For the acquirers, adding functions gives them a better price lever and a lead over their colleagues.

“If Salesforce or Google does not acquire these companies, then their competitors are probably,” Derek Hernandez, a senior emerging tech analyst at PitchBook, told WAN. “The best solutions are currently being adopted. Even if you have a crowned solution, I don’t know that the prospects for staying private ultimately win over going to a larger one [acquirer]. “

This trend offers major benefits for the startups that are being taken over. The Venture market starves to outputs and the current silent period for IPOs does not leave them many opportunities. Being acquired not only offers that exit, but gives these founders room to keep building.

Mohan agreed and added that many data startups feel the pain of the current market with regard to outputs and the slow recovery of venture financing.

“At the moment, acquisition was a much more favorable exit strategy for them,” said Hernandez. “So I think a kind of both parties are very stimulated to reach the finish on this. And I think computer science is a good example of that, where even with a bit of a hairstyle of where Salesforce spoke with them last year, it still, you know, according to their plate.”

What happens afterwards

But the doubt still remains if this acquisition strategy will achieve the goals of the buyers.

As Dhillon noted, the database companies that were taken over were not necessarily built to work easily with the rapidly changing AI market. Plus, if the company wins the AI ​​world with the best data, is it logical for data and AI companies to be individual entities?

“I think that much of the value is in merging the large AI players with the data management companies,” said Hernandez. “I do not know that a self -contained data management company is in particular encouraged to stay that way and, a bit like, playing a third party between companies and AI solutions.”