The first step for any modern analytics endeavor is building a data warehouse. This warehouse will be the foundation of your entire analytics stack.
We’ll help you select your data warehouse and ETL technologies, configure them for you, and optimize the performance of your environment. We’ll also build custom ETL pipelines when necessary, although we always use off-the-shelf solutions where available.
Data modeling is the process of restructuring raw data—cleansing, denormalizing, pre-aggregating, and re-shaping it—so that it supports your analytical use cases.
Data modeling is hard, and we believe it’s the most important piece of your analytics stack. This is where we spend most of our time and brainpower. We build and maintain an open-source product called dbt (data build tool) that hundreds of analysts use to model their data, and we deploy dbt for every one of our clients.
It turns out that counting things is hard. The good news is that most online businesses have very similar measurement challenges and we’ve solved them all a dozen times: marketing attribution, user funnels, subscription revenue, and more…
When it comes to data science at startups, less is more. We’ll help you predict customer churn, forecast sales, and develop a sophisticated attribution model, all without getting lost in the details. We’ll develop your model and deploy to production all in two weeks.
Skip Heap and Mixpanel; we’ll get you up and running with Snowplow Analytics, the tool the pros use. Snowplow is both cheaper and more capable than other event tracking tools, but requires some expertise to configure. Your future self will thank you.
As you scale, you’ll grow your analytics team. We’ll help you find and interview the right people, train them in best practices, and coach them as they begin pushing code to production.