How to Improve Data Quality

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Data quality affects the output of your analytics.

There are two ways to build quality data. One is to capture meaningful data. Second is to have good data input.

To capture meaningful data, you want to focus on data that are relevant to the question you want to answer. For instance, you want to know how big a problem customer churn is. What is meaningful to look at includes the trend in customer churn rate and the reasons for churn. Cost of sales is irrelevant. By focusing on data that are meaningful, you pinpoint the root cause of an issue.

To have good data input, you need easy-to-use tools. Make data input as simple as possible. Minimize guesswork. Minimize the number of data points you want user to input. When users adopt a tool haphazardly, you end up with incomplete and inaccurate data.

These two factors, capture meaningful data and have good data input are key to improve data quality.

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