James Serra contrasts data virtualization with traditional ETL moving data to a warehouse:
Data virtualization integrates data from disparate sources, locations and formats, without replicating or moving the data, to create a single “virtual” data layer that delivers unified data services to support multiple applications and users.
Data movement is the process of extracting data from source systems and bringing it into the data warehouse and is commonly called ETL, which stands for extraction, transformation, and loading.
If you are building a data warehouse, should you move all the source data into the data warehouse, or should you create a virtualization layer on top of the source data and keep it where it is?
Read on for James’s thoughts.