5min chapter

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#116 Value Creation Within the Modern Data Stack

DataFramed

CHAPTER

Is There a Difference Between Data Quality and Data Extraction?

When creating data, you at a huge advantage when it comes to data quality versus data extraction. Data scientists spend all their time cleaning their data and no real time actually using the data to engineer the features and drive model performance. The more sophisticated your use of data, the higher the quality bar has to be. If you're writing unit tests that are simulating your customers, making sure that the data reflects exactly what's being used for is much easier.

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