Best practices for data quality overall
Of course, this book will delve deep into how you can actually clean your data with Power BI, but it wouldn’t be responsible for us to not provide some insight into implementing best practices to prevent dirty data.
As we discussed previously, dirty data can have a significant impact on business operations, decision-making, and overall success. To combat the challenges posed by dirty data, organizations must establish robust data cleaning practices. In this segment of the chapter, we will explore best practices that businesses can implement to effectively tackle dirty data and ensure data quality throughout their operations.
Establishing data quality standards
Define clear data quality standards that align with your organization’s goals and objectives. These standards should include criteria for accuracy, completeness, consistency, validity, and timeliness, as discussed next:
- Developing a data governance framework...
