A major challenge we faced was inconsistent naming conventions across different departments' data sources. With Power BI, I created a central data model that mapped and standardized field names. By leveraging Power Query's capabilities, I automated the transformation and cleansing of data to align with the standardized model. This not only improved data quality but also ensured consistency for reporting purposes. We now have a streamlined and reliable process for addressing data quality issues using Power BI.

One way I have utilized Power BI to address data quality issues in my organization is by setting up data validation and cleansing workflows. By connecting to multiple data sources and using Power Query for data transformations, I have been able to identify discrepancies, missing values, and outliers. I then create visually rich reports and dashboards in Power BI to highlight these issues, enabling the team to take corrective actions. Additionally, I use calculated columns and measures to perform data quality checks and validate the accuracy of information.