The race to unify multi-source datasets is on! For years, companies were encouraged to build their data lakes. Now that they did, 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 root problem is that traditional ETL tools use waterfall ETL frameworks that are not designed to handle that many data sources.
This eBook explains the data unification issues that business and technical teams face with their existing data pipelines. It introduces an emerging industry approach to solving them: Declarative and Collaborative Transformations.
the eBook 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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