Combining and preparing data is a prerequisite for any reporting and analytics project. There are two leading approaches for this process: Extract, transform, and load (ETL) and data virtualization. Use ETL when you want to physically move data from multiple data sources into a single data warehouse. Use data virtualization when you want data to remain in data sources and specify the rows or files to be used for analytics on-the-fly.
Join us to learn the foundational concepts and considerations for these two approaches, and to identify the right path for your reporting or analytics project.
In this webinar, you will learn:
- The differences and use cases for traditional data integration vs data virtualization
- How and why you would want to virtualize multiple data sources
- How to make your data sources user-friendly to support self-service reporting