After its $135 million Series D last week, Monte Carlo has become the latest unicorn in a fast-growing category: data observability, which the startup defines as “an end-to-end approach to enabling teams deliver more reliable data. If you’re wondering how serious data quality issues are, Monte Carlo CEO Barr Moses has an answer: “Data quality issues still plague even the most data-driven companies. Just a few weeks ago, Unity, the popular game software company, cited ‘incorrect data’ for a $110 million impact on its ad business. Moses’ startup isn’t the only one pursuing the data observability market opportunity. On the same day that Monte Carlo revealed its new $1.6 million valuation, competitor Cribl confirmed its unicorn status with a new funding round. “While smaller than Cribl’s Series C, which came close to dwarfing $200 million, Series D values ​​the company at $2.5 billion after the money, according to one source. That’s over $1.5 billion as of August 2021,” noted TechCrunch’s Kyle Wiggers. Any triple-digit deal would be noteworthy in isolation. Two of them in the same space, even more. But what really caught our attention is that the Monte Carlo and Cribl deals were announced now, right in the middle of a broad start-up downturn. We know that large rounds can take time to close and disclose, which means the Monte Carlo and Cribl Series D rounds could reflect the state of the market a few weeks ago. But there is a more recent data point to keep in mind: hiring, which is still happening. On one side of the table, companies are still filling the kinds of positions that create demand for data quality solutions. “Despite the volatility, data engineer and analytics jobs are on the rise and companies continue to hire in record numbers for these roles,” Moses told TechCrunch. On the other hand, data observability startups are hiring. Not just unicorns like Cribl and Monte Carlo, but also competitors like seed-funded startup Sifflet. Could data observability be recession-proof? To find out, we spoke to Moses, as well as Sifflet CEO Salma Bakuk. To round out your first-hand knowledge, we’ve collected notes from two investors familiar with the space: FirstMark partner Mate Turck and Data Community Fund General Partner Pete Soderling. The picture that emerged from our conversations is that the tailwinds for the data observability category as a whole might not translate into profits for each and every startup in the space. Why? We are going to explore.
Rising with the data tide
When we mention tailwinds for data observability, it is because the demand is driven by a broader trend. TL; DR: More and more companies are becoming data-driven and therefore facing the kind of data quality issues that data observability startups need to address. Sizing up a growth opportunity is never easy, but in our conversations we heard that data observation could soon become a universal problem for large companies. “I strongly believe that every company, both tech and non-tech, will need to become not just a software company, but a data company,” Turck said. “That’s why people are excited about the opportunity: It’s a very big market and a big trend.” That the addressable market for data observability is large is one thing. But it would not make sense if the target companies themselves did not consider the need for reliable data. According to Moses, that is increasingly the case in all kinds of industries.
