Blog article: Data Quality Checklist

Published on March 27, 2019

Data Quality Checklist

Creating the perfect dataset isn’t an exact science, but there are steps you can take to ensure that your dataset is optimized for your users. This means ensuring that your open data files are truly open and free of barriers that might prevent your users from working with the data, such as to create visualizations or analyze for research purposes. This checklist aims to give you a sense of simple steps you can take to improve your data files.

1. Remove headings

Before optimization: Your data file should not contain specialized headers or formatting, such as colours and font styles.

Your data file should not contain specialized headers or formatting, such as colours and font styles.

After optimization:

2. Remove all formulas

Before optimization:

After optimization:

3. Clear all formatting

Before optimization:

After optimization:

4. Ensure data is granular

Before optimization:

After optimization:

5. Improve overall structural consistency

Before optimization:

After optimization:

6. Ensure consistent formats

Before optimization:

After optimization: