The race to unify multi-source datasets is on! For years, companies were encouraged to build their data lakes. Now that they have, they're struggling to get the most out of their data. The core problem is that extracting, transforming and loading a large number of data sources in order to unify and orchestrate them is costly and time consuming.
The reason companies struggle so much is that their ETL tools use traditional waterfall frameworks that were not designed to handle that many data sources.
This whitepaper explains the data ingestion and unification issues that companies face with their existing data pipelines. It introduces an emerging industry approach to solving them: Declarative and Collaborative Transformations.
This whitepaper provides technical readers with ETL best practices on how technical teams, including ETL developers, should approach these transformations and achieve Agile Data Preparation.
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