We May Have Seen Only the Beginning of M&A in the Data Space

mergers and acquisitions

By Jeremy Levy, CEO, Indicative

For anyone watching B2B tech in recent years, the action in data has been impossible to miss. Mergers, acquisitions and skyrocketing enterprise valuations have our collective attention. Companies that can take vast amounts of data and operationalize it are hitting home runs left and right. Look no further than Snowflake’s IPO a year ago and Google’s Looker acquisition, to name a pair.

The trend will continue to accelerate. The recent valuations and large rounds of funding have been eye-popping. The data ecosystem is in a frenzy. Month after month, we’re reminded how transformative a time this is for the sector. There is also continued awareness — and acceptance — that companies should be building out their data infrastructure with cloud data warehouses in mind. There is significantly more mainstream adoption of this approach by companies of all types.

The data ecosystem is growing up

The activity over the past couple of years raises the question: What’s the maturity of the data ecosystem? We’re no longer in the nascent stages. It’s still early, but we’re starting to move into a more mature phase around how businesses leverage data.

We’re standardizing on an approach to how to do that vis-à-vis the cloud data warehouse, and the industry is aligning around it, creating much of the enterprise value we see in the market. This new approach also is destroying value for companies that are incompatible with the cloud data warehouse — for example, those that require proprietary storage or pre-analytics data replication.

Why would clients continue to be beholden to monolithic stacks like Adobe when there are best-in-class products that are built to interface with the cloud data warehouse so seamlessly that a company can easily choose the best tools for its stack? Why would they continue to replicate their data time and time again before they operationalize it? The writing for those outdated solutions is on the wall. In addition, companies deserve ownership and control over their own data.

Data warehouses and data lakes will see increasing adoption, and the companies that provide them will see even greater value. The same will be said for companies that can connect directly to the data warehouse and operationalize data without the hassle of data replication or forcing customers to use proprietary storage. So while you have winners like BigQuery, Census and Fivetran on one hand, you see significant threats to stacks like Adobe Experience Cloud and data warehouse-unfriendly platforms like Amplitude and Mixpanel on the other.

One also can’t ignore the companies that have gone public recently, including Amplitude. To some extent, Amplitude’s valuation and filing are wins for everyone in analytics — a massive validation for the market. If the company was founded today, though, it would not have this same level of success because the market is clearly transitioning to the cloud data warehouse model; something Amplitude is simply not compatible with. And while this model has been written about at length, the more tangible predictor of this trend is the continued acceleration of growth at Snowflake and other cloud data providers like Amazon and Google.

Amplitude’s requirements for replicating and operationalizing customers’ data reflect a decades-old approach. Their solution isn’t built for tomorrow. In time, especially given the increased scrutiny of shareholders and earnings reports, the shortcomings of Amplitude’s approach will catch up with them.

New players mean significant opportunity to create value

The barrier to entry into this space is getting much lower. It’s no longer “buy Adobe.” It’s more, “build your own marketing cloud.” Because that’s really what the cloud data warehouse allows adopters to do. Free from the constraints of a proprietary solution, it’s much more feasible to build your own stack. Whether you need an analytics solution or a data quality solution, you can find one that integrates directly into the cloud data warehouse.

Significant opportunity remains for new players to help long-suffering clients address existing data challenges. As Gallup reported last year, only a minority of companies believe they’re making effective use of the data they have. And, consequently, emerging providers will have to be able to demonstrate near-immediate value. Otherwise, customers can quickly try something different. They aren’t handcuffed to a proprietary stack. This competition — and the associated attention and investment — is healthy for the data industry as a whole, even if some legacy providers are under threat.

Still, many questions remain about how the future of the ecosystem will play out. We’ve already seen venture capital flow into the collection and storage portions of the new data architecture. What’s next? Will it be analytics platforms?

There’s a good chance the attention will focus on companies that help customers operationalize data since investment in collection and storage is already running high. Platforms that connect to the cloud data warehouse, leverage data and allow customers to make better decisions would be a natural next area of focus.

We also must wonder about the likelihood of further M&A activity in the space. What are the chances that the prominent players in the market will eventually try to roll up the pieces? What would this look like? If data warehouse companies, for example, acquire collection, analytics and BI companies, would customers still be able to purchase, let’s say, the acquired BI solution à la carte? Or would we be headed toward a new era of proprietary stacks?

Is it, in practice, a natural evolution for dominant companies in industries with decentralized architectures to engage in an M&A strategy, followed by a movement back toward decentralization?

While the data industry is no longer in its infancy, it’s not quite jogging yet either. Legacy, monolithic stacks are clearly under threat, though, and the cloud data warehouse is recognized as the center of modern data architecture. We should expect substantial investment and M&A activity still to come and likely some trial and error before we know what the ecosystem’s prevailing financial strategies will be.



Jeremy Levy is CEO and co-founder of Indicative, the only product analytics platform for product managers, marketers and data analysts that connects directly to the data warehouse. He is a serial entrepreneur and a veteran of New York City’s Silicon Alley. Jeremy co-founded Xtify, the first mobile CRM for enterprise, acquired by IBM in 2013. He also co-founded MeetMoi, a pioneering location-based dating service for mobile sold to Match.com in 2014.