Avoid the unnecessary parts of ETL to maintain data integrity and achieve faster time to value for your analytics initiatives.
Considered a necessary evil until recently, data warehouses and their corresponding ETL processes used to be the only way to efficiently aggregate and analyze large volumes of complex data coming from different data sources. But now there’s a way to eliminate the most painful part of the data warehouse project: preparing and managing data for analysis by flattening, pre-joining, and “re-shaping” data into a workable format. What we at Incorta like to call the “unnecessary parts of ETL.”
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