Posted by: Peter Tran
Best Practices, Business Intelligence, Case Studies, Data Federation, Data Virtualization, Products, Uncategorized
A recently published BI Leadership Benchmark Report lists eleven use cases for data virtualization. The report, Data Virtualization: Perceptions and Market Trends, which includes survey results from 192 BI professionals, was authored by Wayne Eckerson, Director, BI Leadership, a TechTarget research service.
Kudos to Wayne for this a solid list, demonstrating data virtualization’s wide applicability.
1. Data services layer. The most enlightened companies use data virtualization as a services layer for developers and applications to access any data. This creates a universal interface to data, no matter where the data is stored (e.g., data warehouse, operational system, file, Web service, cloud) or what the performance requirements are. If a source system or network link is slow, administrators can use the data virtualization software to cache the specific data in a database to meet systems level agreements.
2. Emergency (SWAT) applications. When the business has an urgent need for a data-intensive application and can’t spend the time or money to physically consolidate the data in a data warehouse or data mart, it can use a team of highly trained developers armed with data virtualization software to create the application quickly and with minimal cost.
3. Real-time applications. Another good use case is to augment a data warehouse or business application with real-time data maintained in elsewhere. Virtualization software queries the data warehouse for historical data and joins it on the fly with real-time data maintained in an operational system.
4. Virtual enterprise data warehouse. In decentralized organizations with relatively autonomous business units, companies often use data virtualization software to create an enterprise view of corporate data for decision making by dynamically querying data held in various business unit and departmental data warehouses and data marts.
5. External data. Another good use for data virtualization software is to augment an application or data warehouse with external data gleaned either from public websites or a subscription service.
6. ETL source. Data virtualization can also be used by ETL tools and other applications as a source of data to populate target systems. Rather than building direct interfaces to each system, the ETL tool relies on the data virtualization layer to access remote data and feed it to the ETL tool.
7. Systems migration. Data virtualization is also a good way to migrate source systems or data warehouses without disrupting downstream applications. As long as the applications are pointed at the data virtualization tool, administrators can swap out backend sources without impacting those applications.
8. Prototyping. Data virtualization is a great way to test the efficacy of a data-driven application before setting it in stone. With data virtualization as a source, developers can experiment with different sets of data before physically consolidating data in a data warehouse.
9. Analytical sandboxes. Data virtualization software liberates analysts from having to write their own SQL and create their own data feeds when analyzing data. This frees them to spend more time analyzing data and less time collecting it and creating data silos.
10. Support diverse BI tools. Many companies have multiple, redundant BI tools that businesspeople use to create overlapping and conflicting reports. With data virtualization software, business users can use whatever BI tool they want and still access the same data elements in the same way using identical semantics.
11. 360-degree view of customers. A classic use case for data virtualization software is to create a 360-degree view of customers by pulling data from different sources, such as order entry system, call center logs, and a provisioning database.”
In addition to the eleven use cases in Data Virtualization: Perceptions and Market Trends, you might also take a look at the ten case studies described Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility.
And for Gartner subscribers, check out data virtualization use cased listed on page 70 of the Hype Cycle for Information Infrastructure, 2012.
How Are You Using Data Virtualization?
Do your data virtualization use cases match any of the above? Or have you found other ways to take advantage of data virtualization’s flexibility?