Modeling your data as described in Correlated's Required Data Model for Data Warehouse Connections will put you in a good place to get started with Correlated. However, as we all know, our data needs evolve over time and there are some last mile calculations that make sense to define in Correlated. Typically, these transformations make sense if they involve adjusting or calculating rows in one or more columns in the provided data models. They aren't a good fit for heavy aggregations that span multiple rows or for joins across multiple tables.
Correlated currently supports last mile transforms via customer support. Your Customer Success Manager has access to the ability to help you configure your data so that it shows up in ways that you and your team can understand. Some examples of last mile transforms we can support include:
If your columns include text fields, we can help you create dimensions that check whether or not a substring exists. For example, if your CS team writes in their notes that a customer has a specific use case, you can search for that specific text and create a dimension that is true with the text exists, and false if it doesn't.
Cross Column Calculation
Some examples of this include:
- Calculating a metric: for example in order to calculate license utilization, you divide total licenses sold by total licenses utilized
- Comparing two columns: for example, you check whether or not the date when someone invited another user is greater than when they upgraded their plan
Updated 4 months ago