Cloud Data Lakes for Analytics/ML: Strategy and Best Practices

Cloud providers serve up lots of powerful, innovative data engines, analytics, and AI services…one at a time. That leaves it up to the customer to provision each one, integrate them, set up role-based access/security, and manage performance, costs, and upgrades. And if you want to integrate on-premises assets, the work cut out for you is greater still.

Given this complexity, how can your organization navigate its journey to a cloud data lake and ML? To learn more, join us for this free 1-hour webinar from GigaOm Research. 

In this 1-hour webinar, you will discover:

  • A strategy to create a cloud data lake for analytics/ML, amid pandemic challenges and limited resources
  • Best practices for navigating growing cloud provider ecosystems for data engines, analytics, data science, data engineering and ML/AI
  • How to avoid potential pitfalls and risks that lead to cloud data lake delays

Why Attend

A cloud data lake is a powerful platform for modernization, migration, and digital transformation. The cloud empowers enterprises to collect all data and use multiple analytics engines, as well as machine learning (ML) platforms, to drive competitive advantage and insight.



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