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As businesses have modernized data processes to prioritize self-service and agility, the need for more “analysis ready” data, faster, has led to the advent of modern data preparation solutions. Data preparation platforms prioritize ease of use, rapid iteration, and machine learning-guided functionality to make the traditionally-tedious process of data cleaning more efficient and accessible to non-IT users. In comparison, ETL technologies were designed to support operational data pipelines with limited numbers of data consumers, prioritizing stability over speed. Organizations still need both, but how do you determine when to use which approach?

In this webinar recording hear Ovum Senior Analyst, Paige Bartley for a presentation on the evolving role of data preparation and ETL solutions. Bartley will review her latest research on the data preparation market and why it’s one of the fastest growing segments of the data management industry. Davis will share best practices and real world examples of organizations that have successfully implemented data preparation alongside ETL as part of their analytics modernization initiatives.

Watch this webinar to learn:

  • Why now? What enterprise needs were unmet before data preparation?
  • How to balance speed and self-service with data governance and control
  • Criteria for determining which processes are best for self-service data preparation vs. ETL

Featured Speakers:

Will Davis, Director of Product Marketing – Trifacta
Paige Bartley,  Senior Analyst – Ovum

""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.""