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3 Mistakes in Data Prep

Best-practice guide to avoid slips when turning raw data into ready-to-use inputs for business intelligence.

The first step is the most important

Data preparation is one of the most challenging and yet overlooked phases in the data value chain. It lays solid foundations for all future data analysis, so, If done poorly, it leads to bad data that may damage several areas of the business.

This booklet discusses the most common mistakes in data preparation and shows how to avoid them.

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  1. Data preparation mind-set: understanding the process before solving it.
  2. Data preparation tools: no-code integrated tools can make a difference.
  3. Data preparation skills: converting leaning into productive actions.