Accelerated Data Science in VAST DataBase

Data science workflows are often constrained by data movement, disconnected tools, and limited access to large datasets. These limitations slow experimentation and make it difficult to work efficiently at scale.

In this webinar, we demonstrate how the VAST DataBase enables data scientists to access and work directly on large datasets using Python and native APIs. We will walk through real-world examples including time series and geospatial analysis, and show how ML inference can be executed at scale.

We will also show how the VAST AI OS consolidates data storage, analytics, and AI execution, eliminating the need to move data between systems and accelerating the data science lifecycle.

Key Takeaways

  • Why data movement limits data science and AI workflows

  • Using Python and native APIs on the VAST DataBase

  • Scaling ML inference across large datasets

  • Deep dive into time series and geospatial analytics

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