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5 Data Quality Tools You Should Know About
Spectacles, Datafold, and more
Data quality ensures that an organization’s data is accurate, consistent, complete, and reliable. The quality of the data dictates how useful it is to the enterprise. Ensuring data quality — especially with the sheer amount of data available to today’s enterprises — is a tremendously complex beast. To do this effectively, the modern enterprise relies on data quality tools.
In this post, we will consider five data quality tools and see how they can help you in your data journey:
- Great Expectations
- Spectacles
- Datafold
- dbt (Data Build Tool)
- Evidently
Before we dive in with our tools, let’s first set the stage for why ensuring data quality is a business essential.
Why Bother with Data Quality?
Today’s businesses are dependent on data more than ever before. According to a recent Gartner data quality market survey, poor data quality costs enterprises an average of $15 million annually. Erroneous data can result in lost business opportunities, bad market reputation, low customer confidence, and significant financial losses.
