Summary

In this chapter, we learned about what needs to happen with data quality after the intense effort of a budgeted data quality initiative. We learned what causes data quality issues to re-occur and how we can minimize that recurrence. We also learned about the need to keep up with business change and manage the baseline of rules effectively as time passes. Then, we learned about how to transition data quality remediation from a fully managed initiative-based process to an embedded activity in a business as usual team. Finally, we learned how to transition from a single initiative into a longer-term roadmap of activity that fully transforms the data quality of your organization.

We’ve now been through the entire data quality improvement cycle that we outlined in Chapter 2. In the final chapter, we will highlight the key best practices and the most commonly made mistakes in data quality work before finishing this book by looking at how innovation might change the field...