The data industry is on the verge of an active transformation.
The market is established. And if the flow of the deal in the last two months is any indicator – with Databricks buying a neon for $ 1 billion and Salesforce breaking Cloud Informatica management company for $ 8 billion – the momentum is built for more.
The companies acquired can range in size, age and dining area within the data stack, but they all have one thing in common. These companies are purchased in the hope that the technology acquired will be the part you need to get businesses to adopt AI.
At the surface level, this strategy makes sense.
The success of AI companies and AI applications are determined by access to underlying data. Without it, there is simply no value – a belief that Enterprise VCS shares. In a TechCrunch survey conducted in December 2024, Enterprise VCS said the quality of the data was a key factor for the newly established AI companies to distinguish and achieve. And while some of these companies involved in these agreements are not newly formed businesses, the feeling is still found.
Gaurav Dhillon-the co-founder and former Managing Director of Informatica and his current president and chief executive of Data Integration Company Snaplogic-held this in a recent interview with Techcrunch.
“There is a complete reset to the way of managing data and flows around the business,” Dhillon said. “If people want to take advantage of the urgent need AI, they must repeat their data platforms in a very big way and here I think you see all these data acquisitions because this is the foundation that has a healthy AI strategy.”
But is this strategy to remove companies built before a world after Chatgpt the way to increase AI businesses in today’s fast -paced market innovation? This is unclear. Dhillon also has doubts.
“No one was born in AI, that’s just three years old,” Dhillon said, referring to the current market after Chatgpt AI. “For a larger company, to provide AI’s innovations to re -imagine the business, in particular the business, it will take a lot of rearrangement to happen.”
Fragmented landscape
The data industry has evolved into an extensive and fragmented tissue over the last decade – which makes it mature for unification. All he needed was a catalyst. From 2020 to 2024 only, more than $ 300 billion were invested in newly established companies in more than 24,000 deals, according to Pitchbook data.
The data industry was not immunity to trends observed in other industries such as SAAS, where the Committee on the company of the last decade has resulted in many newly established companies being funded by businessmen of capitalists targeting only one particular area or in some cases built around a single feature.
Today’s industry standard combines a bundle of different data management solutions, each with its own special focus, does not work when you want AI to drag around your data to find answers or create applications.
It makes sense that larger companies are trying to move the newly established businesses that can connect and fill the existing gaps in their stack. A perfect example of this trend is the recent acquisition of Fivetran in May – which yes, was done in the name of AI.
Fivetran helps companies transfer their data from various sources to cloud databases. For the first 13 years of her business, she did not allow customers to transfer this data behind these databases, which is exactly what the inventory offers. This means that prior to this acquisition, Fivetran customers need to work with a second company to create an end -to -end solution.
To be clear, this is not intended to throw a shadow on the Fivetran. At the time of the deal, George Fraser, co -founder and chief executive of Fivetran, told TechCrunch that while moving the data inside and outside these warehouses it looks like two sides of the same currency, it is not so simple. The company even tried and abandoned an internal solution to this problem.
‘Technically, if you look at the code down [these] Services, they are really quite different, “Fraser said then.” You have to solve a fairly different set of problems to do this. “
This situation helps to depict the way the data market has been converted in the last decade. For Sanjeev Mohan, a former Gartner analyst, who now runs Sanjmo, his own data trends consulting, these scenarios are a great guide to the current wave of integration.
“This integration is guided by customers who are bored with a multitude of products that are incompatible,” Mohan said. “We live in a very interesting world where there are many different data storage solutions. You can make an open source. They can go to Kafka, but one area where we failed is metadata.
Good for newly established businesses
The wider market plays a role here too, Mohan said. The newly established businesses are struggling to raise funds, Mohan said and the exit is better than having to finish or load debt. For buyers, adding their features gives better pricing leverage and advantage against their peers.
“If Salesforce or Google do not get these companies, then their competitors are likely,” said Derek Hernandez, a senior technology analyst on Pitchbook, TechCrunch. “The best solutions are currently acquired. Even if you have an award -winning solution, I don’t know that the prospects to stay private eventually win to go to a bigger one [acquirer]. ”
This trend brings great benefits for acquiring newly established businesses. The market for business moves is starving for exits and the current quiet period for IPO leaves them many opportunities. The acquisition not only provides for this output, but in many cases it also gives these founding spaces to continue to build.
Mohan agreed and added that many data businesses feel the pains of the current market in terms of exits and slow recovery of business funds.
“At this point, acquisition was a much more favorable exit strategy for them,” Hernandez said. “So I think, the kind of two sides is very motivated to get to the finish line. And I think Informatica is a good example of it, where even with a piece of haircut from where Salesforce was talking last year, it is still, you know, it was the best solution, according to their council.”
What will happen next
However, doubt remains whether this acquisition strategy will achieve the objectives of buyers.
As Dhillon pointed out, the database companies acquired were not necessarily designed to work easily with the rapidly changing AI market. In addition, if the company with the best data wins the world AI, will it make sense for data and AI companies to be separate entities?
“I think a lot of value is the merger of AI’s most important players with data management companies,” Hernandez said. “I do not know that an autonomous data management company is particularly incentive to remain so and somehow play a third part between businesses and AI solutions.”
