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Six Data Prep Steps to Optimize Cloud Data Lakes

Ready to take the plunge into a cloud data lake? Don’t dive in just yet.

Most of the data filing your cloud data lake is raw, unstructured, and rife with data quality problems. If you’re going to get maximum value from your cloud data lake investment, data preparation is critical.

TDWI has created a readiness checklist to guide you through six steps your organization should take to improve agility, productivity, and consistency when preparing data for a cloud data lake:

  1. Choose a data preparation solution that natively integrates with your cloud platform
  2. Use data preparation to increase efficiency and coordination among stakeholders
  3. Don’t rebuild what works; choose the right use cases
  4. Empower users with self-service while maintaining data governance
  5. Ensure data quality with at-scale and continuous validation
  6. Publish and operationalize preparation for downstream analytics and machine learning

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""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.""