Quality Control – Row level changes are hard to attain between versions.We designed CDF to make coding even simpler and address the biggest pain points around CDC, including: However, even with the right tools, CDC can still be challenging to execute. Many customers use Databricks to perform CDC, as it is simpler to implement with Delta Lake compared to other Big Data technologies. We are happy to announce the exciting new Change Data Feed (CDF) feature in Delta Lake that makes this architecture simpler to implement and the MERGE operation and log versioning of Delta Lake possible! In addition, the different tables in the architecture allow different personas, such as Data Scientists and BI Analysts, to use the correct up-to-date data for their needs. CDC and the medallion architecture provide multiple benefits to users since only changed or added data needs to be processed. The medallion architecture that takes raw data landed from source systems and refines the data through bronze, silver and gold tables. Typically we see CDC used in an ingestion to analytics architecture called the medallion architecture. Change data capture (CDC) is a use case that we see many customers implement in Databricks – you can check out our previous deep dive on the topic here.
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