K2View Enterprise Data Pipeline keeps your data lakes and data warehouses in sync with your data sources, based on data sync rules you define.
You can configure and automatically apply data filters, transformations, enrichments, masking, and other steps crucial to quality data preparation.
Data pipeline flows are iterative and can be set up, tested, and packaged for reuse. They can be automatically invoked to operationalize data preparation and accelerate time to insights.
Data scientists can also reproduce previous sets of data and access any historical version of that data.
Data changes can be ingested into your data stores in any data delivery method of your choice: from bulk (ETL), to data streaming, to CDC (Change Data Capture), and messaging.
So, your data is always complete, up-to-date, and consistently and accurately prepared, ready for analytics and operational workloads.