If I had to choose two Key Performance Indicators for a data platform team: - Time to market for new datasets/pipelines - Data Downtime (periods of time when data is inaccurate)
Why? - Producing side: Scaling for data volumes is solved, now scaling is about adding new datasets/pipelines, especially as feature teams will take on data ownership and micro services will deliver data as a first class deliverable in addition to the service API. - Consuming side: As companies become more data-driven and sophisticated in their use of data, expectations on accurate, reliable and timely data will grow in importance.
What are yours, and why? Please share your thoughts, we all benefit from discussions and ideas in this topic. My experience is that data platform team are instrumental in businesses being able to set up and track performance of various teams, but ironically rarely have good performance KPIs themselves.