In our technology careers, Jeremy and I have seen first hand the advantages of being data-driven. From improving consumer products through rapid experimentation, to optimizing advertising spend to fuel growth, or even helping Instacart shoppers navigate stores to find your groceries. Data is fueling the break-out innovation behind many successful companies today.
But despite the amazing tools available in the modern data stack, there is a dirty secret lurking inside of most data organizations.
The reality is, much of the data that companies ingest, store, and query is incomplete, missing, corrupted, or improperly used. As a result, incorrect decisions are made with faulty data and data driven products and processes routinely underperform.
This hidden “data quality tax” significantly affects financial outcomes for many companies. Their growth potential is limited, their customers and partners become frustrated, and their profitability erodes.
Meanwhile, data engineers are overwhelmed responding to complaints about missing or incorrect data and performing complex data fixes by re-running pipelines and backfilling data sets.
Jeremy and I have seen many of these issues first hand. And in our prior roles, we always wished we had a tool that would allow data teams to quickly and easily validate their data, without doing a ton of work. A platform that would instantly tell you when a 3rd party data feed was missing important data or alert you when a key table was out of date or was missing rows from a particular segment.
So we built Anomalo. And as we describe in Airbnb-quality data for all, you can use Anomalo to quickly and easily develop the kind of data validation processes used by the most successful technology companies.
We are also grateful to our angel investors who have already helped immensely with startup advice, product feedback, and customer introductions. So thank you to Anthony Goldbloom, Peter Skomoroch, Sam Shah, Ryan Noon, Josh Wills, Hilary Mason, Pete Kazanjy, Jason Heidema, Adam Nash, Max Mullen, Serkan Piantino, Auren Hoffman, as well as Pete Soderling and the Data Community Fund.
And of course, if you want to easily validate and ensure the quality of your data, please drop us a line.