The analytics pipeline can be compared to a domino chain. Every domino is a step in the operations that provides a consistent and high-quality output. Every change you try to make in the chain needs to be executed with precision for it can cause all stones to fall, causing a domino effect.
Every update or small adjustment triggers a change in the pipeline. It is therefore advised to validate and verify changes, which often takes longer than the change itself.
Data lineage describes the complete data life cycle by providing insight in the data flow from start to finish. It uncovers how data flows from the data sources to the data consumers.
Data Warehouse Automation allows you to detect changes within the data structures of your data sources and will generate the changed data pipelines.
Data Warehouse Automation
Data Warehouse Automation gives an answer to structural and scaling problems that are common to initial data warehouse projects. Raise your return on investment by delivering intermediary results and make re-engineering possible during the course of the project.