Data Quality & the Importance of Reliable Data

Data quality is the measurement of data in terms of accuracy, completeness, consistency, validity, uniqueness and timeliness. It enables businesses and organizations to quantify and better manage their data.  

Machine learning (ML) is one of the biggest value-adds for businesses, and at the heart of every machine learning challenge is the input data. A machine learning model is only as good as the data that goes into it, which is why, in the world of supervised learning, data scientists rely on a set of accurately labelled data points.

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• What is Data Quality? 
• Why is Data Quality Important with Machine Learning?
• Challenges to Reliable Data
• Managing Unreliable Data