Data Analytics: Step 1

One of the things I remember from my Computer Programming 101 class in college is the acronym GIGO which stands for Garbage In Garbage Out. The idea is a program can only be as good as the data it uses or the code that it is utilizing. This principle is by no means outdated and applies perfectly to data analytics.
The starting place for all data projects should be the quality of the data. There are two simple factors questions you can ask to determine the quality or relevance of your data.

  1. Is your data current or outdated? Are you trying to make real time decisions with data that is a month old? Then your data analysis may not be trustworthy.
  2. Is your data accurate? Was your data entered by hand or by a system? If there lots of discrepancies or variations in the data then it can’t be trusted.

The only way to have a quality data analysis is to start with quality data. No matter how good your data models are if they are based on bad data they’re useless. Garbage In. Garbage Out.

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