Great BI tools, and still no simple answers
4 November 2026 · 1 min read
Over the past few months we have spoken with a number of senior data leaders and CTOs. Some of them run large, well-funded data platforms with every modern tool you could name. The conversations were amazing, and gave us strong confidence to proceed, as well as some ideas to consider further.
Four things we heard again and again
1. Moving data is the easy part now. “Moving data is a solved problem”. The hard part is knowing what the data means, where the source of truth is and who owns it.
2. Source documentation is written for the people who run the application. The docs aren’t for data consumers, data teams work out the meaning themselves, from schemas and raw values.
3. Problems show up where the data gets used. A number looks wrong on a dashboard, someone digs back through the pipeline, and the fix often gets patched in at that point, far from where the problem started.
4. Definitions multiply. One leader joked about having 16 definitions of ARR. Every team has a version, and nobody is quite sure which one reaches the board.
Most of these organisations have a data dictionary. Several people told us it rarely matches how the systems actually behave.
These are smart teams with good platforms. They still spend a lot of expensive time working out what their data means before anyone can use it. That's the problem we're working on at Neuroplastiq.
Would you like to rapidly build a common data model and have it easy to stay up to date? Let us know if you want to see what Neuroplastiq can do.