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Moving Analytics to the Cloud?

Survey of 600+ data workers reveals biggest obstacles to AI/ML in the cloud

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The quest for the insight-driven enterprise has spurned a mass exodus to the cloud. But cloud data ecosystems can be very complex with multiple data storage and processing options. Most organizations are struggling with how to accelerate analytics in their data lake environments. For example, many organizations are struggling to figure out how to manage data across all the services offered by Amazon Web Services. Data can be stored and analyzed in a variety of different AWS services including Amazon Redshift, EMR, and S3 with Athena.

Modern data preparation platforms bring the discipline of DataOps to complex cloud environments. Data provisioning, self-service, and intelligent data preparation powered by machine learning are enabling agile methodologies that had previously been relegated to application development.

Join leading IT analyst firm Enterprise Management Associates (EMA), Trifacta, and Amazon Web Services (AWS) for a webinar that will help you:

  • Understand technology trends that simplify your analytics modernization journey
  • Learn best practices to operationalize data management on AWS
  • Establish operational excellence leveraging AWS data storage and processing
  • Accelerate time-to-value for analytics projects with data preparation on AWS

""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.""