Most organizations address data quality reactively, after errors are made and, as a direct result, suffer from bad data. It takes a special person, a “data provocateur,” to challenge the status quo, address data quality pro-actively by “getting in front” of the issues, making a huge improvement, and, in effect, showing the rest of the company what is possible. This highly-interactive workshop provides the essential steps to becoming an effective provocateur.
You Will Learn
- What a data provocateur can accomplish.
- A four-step process for becoming a successful provocateur.
- How to baseline quality using the Friday Afternoon Measurement.
- A simple process for understanding customer needs.
- A simple process for finding, and eliminating, root causes of error.
Anyone who needs data to do their jobs effectively, including:
- Those who are not getting the quality data they need from corporate DQ functions,
- Data quality managers, who need to demonstrate successes more quickly.
- Data scientists and others who spend more time dealing with mundane data quality issues that they do using the data.