Sometimes I am surprised how seemingly completely different areas are closely connected. When I built the first dashboards for my data to use our solutions, I saw that the quality of the data had room for improvement. Some data was missing or outdated. And yet I was already able to present insights and results for our product management.
Last week, I spoke to a friend of mine who works as a chemical assistant in a government agency and analyses soil samples. She also collects data and provides dashboards and overviews. Her data is also incomplete or incorrect. But she too can generate valuable insights.
This was followed by a conversation with another friend who collects data on electricity generation at an energy producer and prepares it for reports to the management. He, too, is struggling with data quality.
I find it very exciting that all these different departments end up having the same challenges. And the same two strategies always emerge:
- show the best you can with the data you have.
- work on the quality of your data.
But don’t try to boil the ocean. You will never have 100% correct data. Make sure that the errors don’t twist the message of your dashboards. I work with two views of our data: An internal view that reveals gaps in quality, and an external view that helps our stakeholders make decisions. In doing so, we have to provide interpretation aids as long as there are gaps in the quality of the data.
And most importanty, we need t clearly state the quality of the data when we build dashboards.