Today’s BI tools often serve as glorified interfaces for accessing and exporting out datasets. As we “democratize data,” we are unfortunately shifting the heavy analytics lift to the end user.
When I transitioned from leading data teams to driving growth and business initiatives, I was often surprised by how much effort went into building and maintaining comprehensive dashboards, only to see end users treat these dashboards as “source data” for further analysis in spreadsheets.
As a macro trend, this is unsurprising. Measurement and visibility into business performance are now table stakes. Organizations now want to:
However, these workflows are under-served by traditional BI tools, where the abstraction of a “dashboard” is simply inadequate. Many data and business teams have come to accept this reality as normal, and as a result, the analysis culture evolves in one of two ways:
We can break free from these patterns by building the next level of abstraction on top of data models and automating common analytical workflows.
By implementing metric trees that capture and standardize underlying business processes, and building algorithms that automate common analysis calculations, we can push the frontier of analytics forward.
In this world, data teams design and implement metric trees in collaboration with the business stakeholders, and business users can access outputs of complex analysis with just a few clicks.
I’m genuinely excited about this future, and how Trace is positioned to help make it a reality.