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Cleaning the online retail dataset

You're a data engineer at Global Retail Analytics. Your manager has flagged quality issues in the online_retail dataset - missing customer IDs, duplicated rows, and cancelled orders are skewing weekly reports.

Before any analysis can begin, you need to define an explicit schema, diagnose the data quality problems, and build a cleaning pipeline that removes invalid records.

This exercise is part of the course

Data Transformation with Spark SQL in Databricks

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