Question

List some of the myths of data virtualization and explain why they are not necessarily true.

Answer 1

Myths of data virtualization and why they are not necessarily true:

1. Data virtualization can't perform as fast as ETL: By extracting only the pieces of data used for analytics instead of full copy of data, Data virtualization is faster than ETL.

2. Data virtualization is too complex: Software is available that will allow users to query multiple sources of data from any of several emerging data sources. This myth is propagated by a lack of knowledge.

3. Implementing new data technology isn’t cost effective:Data virtualization costs have become comparable to building a custom data center.Scripting through applications like Puppet to automate repetitive tasks.The number of IT personnel is much fewer which is needed to process Agile Business Intelligence tasks.

4. The purpose of data virtualization is to emulate a virtual data warehouse: Data virtualization is more beneficial if data marts are connected to existing data warehouses to augment them. So data virtualization can be used as a data warehouse.

5. Data virtualization requires shared storage: Data virtualization works with many type of data storage like Direct attached storage(DAS). Direct attached storage can be presented as unique data stores to the hypervisor and used the same way as any other data store.