The Missing Piece of the Modern Data Stack: Our Investment in Transform

Data requests start with a simple question; what was our revenue last month? But there is rarely a simple answer. One dashboard says revenue was $1M last month. Another says it was $900k. And another says it is $500k. Which is correct? Every day executives make decisions with incorrect data that have a huge impact on their businesses. While business users spend time chasing the “right” answers, data engineers and analysts are spending hours debugging metrics that don’t add up.

I saw this first hand as a member of the data team at LinkedIn. We built data pipelines to compute the engagement of different algorithms. One team would filter a certain way when computing click through rate and another team would use a slightly different computation. It was impossible to know who was right. Two dashboards would show different numbers, and we would spend a week debugging the issue only to find both dashboards were incorrect. This led to a huge amount of engineering time lost and ultimately a lack of confidence in the metrics driving key business decisions.

Thankfully, the data team at LinkedIn had the resources to build their own solution called UMP (Unified Metrics Platform), which ensured all teams were using consistent metrics. UMP spread through LinkedIn like wildfire and was used by everyone from engineers to PMs to executives. If your metrics weren’t in UMP, no one trusted your results. The pain point around metric consistency is one felt all across the data world and many companies like Airbnb and Uber built their own in-house solutions as well.

Over the last few years, as I have moved from data engineer to investor, the data stack has changed dramatically. Hadoop has been replaced with the data warehouse leading to huge improvements in how fast people can get their questions answered. But speed of analytics only matters if the results are trustworthy. Is the answer right? Can we trust this metric? More than ever before, organizations are leveraging massive amounts of data, across more stakeholders, with higher stakes decisions. Getting metrics right is no longer a luxury, it is critical.

Enter Transform

Transform is the first centralized metrics store. It sits on top of the data warehouse and allows all company metrics to be stored in one place, so BI dashboards, internal tools, data quality products, and CRMs to all use consistent metrics. With Transform, there can now be one definition of revenue used by every tool and an entire company can think in higher level metrics like revenue, users, and retention instead of tables and pipelines.

We first met Transform’s three co-founders Nick Handel, James Mayfield, and Paul Yang when the company was just a slide deck — and immediately knew this was a company we wanted to be a part of. We share a vision on the evolution of the space given our investments in Looker and Snowflake, and Nick, James, and Paul couldn’t have been a more compelling team to go build it. Having seen the problem first hand at Airbnb, they were ready to bring their solution to organizations across the world.

We co-led a $4.5M seed in Transform with Index Ventures in February 2020. Since then, Transform has hired an incredible team out of companies like Slack, Asana, Opendoor, Airbnb, Facebook, StockX, and Auth0 and onboarded many world-class companies to the platform. Given our excitement, we doubled down for the $20M Series A with Index, and are thrilled to invest alongside Box Group, Fathom Capital, Worklife Ventures, and an impressive group of angels including Elad Gil, Lenny Rachitsky, and Jason Warner.

Transform is hiring across the company; if you’re interested in building the future of data consumption check out Transform.co or send me a note!