When selecting data to profile, consider the following best practices to ensure data is accurate, reliable, and useful for your analysis.
| Best practices | Description |
|---|---|
| Start with a clear understanding of the data and its purpose | Understand the business context and the questions that the data is intended to answer. |
| Select relevant data | Only select data that is relevant to the analysis or business problem. |
| Consider data quality | Profile data that has been cleaned and preprocessed to ensure high data quality and reliability. |
| Use a representative sample | If profiling a large data set, use a representative sample of the data to ensure that the analysis is accurate and reliable. |
| Be aware of data size | Be aware of the size of the data. Huge data will take more time to profile. |
| Consider data freshness | Select data that is as up-to-date as possible. Stale data may not provide the most accurate or useful results. |
| Consider data lineage | Understand the data lineage of the selected data. This will help you to understand the data's provenance and the processes applied to it. |
| Collaborate with experts |
Collaborate with experts in the field or with the business area to ensure that you are selecting the right data. |
By following these best practices, you can ensure that you are selecting high-quality data that will provide accurate and reliable results for your analysis and that the data complies with the organization's policies and regulations.