From the course: Turning Data into Strategies
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Explore data quality
From the course: Turning Data into Strategies
Explore data quality
Let me tell you a story. I was in my early 20s and was working as a data analyst. At one point, my manager asked me to find an older data set on car market trends. Accessing the data was not an issue as the data was stored on the company's server. But when I opened the file, I couldn't understand the variable names because something important was missing, a data dictionary. On top of that, many data points were missing, and also there was no explanation of how the data was collected. I was stuck. I didn't know what to do, and had to go back to my manager to get help in assessing the quality of the data. As a data analyst, sometimes you are faced with data that is confusing and might not know what to do with it. In this lesson, we are focusing on data quality. You learn how to identify data anomalies and document your data to ensure precise and trustworthy analysis. Ready? Let's dive in. First, spot check for anomalies. Data sets are rarely perfect. That's the beauty and at the same…
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