Effective data mining techniques are essential to using data for competitive advantage.

Data mining is a process that turns large volumes of raw data into actionable intelligence, and it's used by a wide variety of industries.

A new survey of data scientists found that they spend most of their time massaging rather than mining or modeling data.

How can companies ensure they’re producing clean, extensible, enriched insights that are accessible to colleagues across an organization and partners alike?

Data mining may still have a disproportionately negative effect on protected classes if the criteria that reliably predict some job-related quality also happen to correlate with class membership.

It’s time for the music industry to shift from endless data clean-up to a strategy of quality at the source, and transform data from a liability into a reliable asset. The following comes from Natalie ...

Data Quality: The accuracy and reliability of the insights from data science depend on the quality of the data. Inaccurate, incomplete or biased data can lead to incorrect conclusions.

A new Bloomberg report on the Kitwe dam disaster in Zambia suggests that its impact is 30 times worse than first estimated, ...

Struggling with messy data? See why Power Query is faster and easier than Python for cleaning and transforming data. Python vs Power Query ...