Best Practices

Understanding owl activities and what the key/date columns mean for each

• ​https://docs.owl-analytics.com/dq-visuals/​

• Training with Owl-team Zoom/On-site support

• Running with sample data

• Introducing anomalies on sample data and running an owlcheck to see the anomalies.

Using the tool with practical scenarios

• Having Well Defined Use Cases

  • Determine a single table (dataset) that you would like to scan

  • Have an expectation of what you would expect Owl to find in this dataset

  • Understand which activities would capture the expected findings

• Target internal datasets with known data issues

• Historical Comparisons:

  • If pre-cleaned data is available with data findings that have been cleaned via legacy methods such as internal rules, run these datasets and compare the results from Owl to Internal findings.

• Work with data owners to understand findings or review expected findings