Large Scale Data Profiling with whylogs and Fugue on Spark, Ray or Dask

Profiling large-scale data for use cases such as anomaly detection, drift detection, and data validation

Motivation

Data pipelines have the potential to produce unexpected results in a variety of ways. Anomalous data can cause data to be scaled incorrectly. Machine learning model drift can lead to reduced prediction accuracy. Failures in the upstream collection could cause null values as the data pipeline executes. How do we safeguard against these failure cases? …

big data dask data data profiling data science fugue logging pandas profiling ray scale spark