Data science requires vast amounts of data. And that too from multiple sources. Data virtualization integrates the data across these disparate sources and provides a unified view of the data to data science algorithms. With it, data scientists can deliver important answers to business questions that enable the business users to perform their functions efficiently.
In this session, you will learn:
- The data science requirement at Prologis - cost optimization
- How data virtualization can be used to support data science projects
- Architectural setup with data virtualization feeding data science algorithms