In this blog, we’ll discuss all things data quality and data observability. We’ll present interviews with leading data scientists, and we’ll discuss our own working building data observability solutions for data engineers and data scientists working in a broad range of industries.
Consistent pipeline behavior is critical for any data process. You can use Data Culpa Validator to ensure consistent operation of pipelines as well as data at rest in databases, data lakes, and data warehouses. This introduction shows you how to validate your results...
Here’s what we’re writing on Medium:
The Data Quality Gap (June 11, 2020)
4 Lessons for Data Scientists from the UK’s A-Levels Algorithm Debacle (August 18, 2020)
Feel free to reach out to us!
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