From streamlining the flow of information, to making business intelligence available faster at scale along with safeguarding data and lowering cost of ownership, the data warehousing process has evolved massively. Data warehouse automation now plays a critical role in that pursuit. In order to automate planning, modeling, and integrating the data lifecycle, data warehouses are now using various ETL – extract, transform, and load – solutions that run on advanced design patterns and processes.

ETL has been an essential process since the dawn of big data. Today, organizations are increasingly implementing cloud ETL tools to handle large data sets. It was common in the past for organizations to have several separate ETL resources. But, with data sets becoming larger by the day, unified ETL tools have become crucial for data integration needs of enterprises.

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