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Does the shift to modern, agile data management practices mean EOL for ETL? Today’s data-driven organizations are moving data into flexible centralized storage structures, such as data lakes and cloud blob storage, and using new data preparation technologies to assess and transform data for analytics success. 

This eBook explores the shift from ETL to data wrangling in the cloud. It documents each phase in the evolution:

  • Creating and filling the data lake
  • Moving data to the cloud
  • Decoupling data movement from data preparation
  • Supplanting data transformation with data preparation
  • Retiring ETL and embracing data wrangling

""Trifacta brought an entirely new level of productivity to the way our analyst and IT teams explore diverse data and define analytic requirements. Our users can intuitively and collaboratively prepare the growing variety of data that makes up PepsiCo’s analytic initiatives.""

""We were actually able to shave the amount of time it took to do the analysis by [a factor of] six. Rather than having to do a tremendous amount of analysis, we’re actually readily able to start getting incremental data products out quickly.""