Venyu Blog

As I’ve documented time and again I’m a big fan of to-the-point lists that detail reasons you should consider in migrating your infrastructure to the cloud or, in this case, a dozen very compelling reasons to virtualize your data.

 As found in this great Sys-Con column by Robert Eve “Twelve Good Reasons to use Data Virtualization,” the explosion of data – in 2010 more than one trillion gigabytes and projected to grow another nine fold over the next five years – requires a remedy proportional to the challenge. That solve is data virtualization, which according to Eve has been “purpose built to address these challenges through an agile, high-value data integration approach” that also, serendipitously, provides business with the timely data it needs, even if the data required spans multiple silos.

The twelve reasons cited by Eve include:

1. Data Virtualization Delivers Value Five Ways – Data virtualization delivers value to business functions and IT operations in a number of measurable ways including top-line revenue growth, risk reduction, time savings, technology savings and staff savings.

2. Data Virtualization Discovers Complex Data – Data virtualization platforms include a discovery option that provides the simplest and fastest way to find and explore enterprise data and prepare the models needed by your downstream data integration and application development processes.

3. Data Virtualization Abstracts Source Data – Enterprises and government agencies use data virtualization to resolve the mismatch between how their data is stored (formats, structures, APIs, etc.) and how their data is used in reports, portals and other consuming applications mismatch.

4. Data Virtualization Accesses Diverse Data – With diverse sources across multiple locations, often outside the firewall, enterprises use data virtualization to facilitate source data access using standard approaches including ODBC, JDBC, and ADO.NET for relational, JMS and SOAP for Web services, APIs for packaged applications and legacy systems, Java for procedural interfaces, and adapters for mainframes.

5. Data Virtualization Federates Data Silos – Adding new meaning and value to previously isolated data, data virtualization lets organization seamlessly federate data silos.

6. Data Virtualization Delivers Timely Information with High Performance – High-performance query techniques and a number of advanced caching methods allow data virtualization to ensure up-to-the-minute data whenever needed.

7. Data Virtualization Secures Data – Data virtualization leverages LDAP and Active Directory authentication to enforce user-based data security rules already established in source and consuming systems.

8. Data Virtualization Complements Physical Data Consolidation and ETL – Leading organizations understand that a portfolio of data integration techniques and technologies are required to effectively meet today’s wide range of needs.

9. Data Virtualization Meets both Project and Enterprise Level Requirements – Most organizations initially deploy data virtualization to meet project specific integration requirements and then expand adoption across their enterprises.

10. Data Virtualization Accelerates SOA Transition – Data virtualization works in conjunction with other SOA tools such as Enterprise Services Buses (ESBs), Registries, and Application Servers, so you enterprises can leverage prior SOA technology investments.

11. Data Virtualization Is Easy to Build and Use – Data virtualization platforms simplify, accelerate and improve each of the major steps in the typical software development lifecycle process.

12. Data Virtualization Fits Neatly Within an Existing IT Environment – Data virtualization supports key industry standards such as ODBC, JDBC, ADO.NET, SOAP, JMS, SQL, XQuery, Java, and REST as well as open APIs for metadata and administration.   This enables data virtualization to easily leverage existing metadata, data, hardware, and software assets and to run in any environment without restriction.

Eve concludes his post with the domino-like effect established by storage, server and applications virtualization which, logically and conclusively leads to data virtualization.  The result? Savings in time, staff and technology costs while enabling enterprises and agencies to increase revenue and productivity and reduce risk.

And now you have the same number of reasons as any jury in good standing would have in judging a case: Twelve good reasons to choose data virtualization, each a flagstone along the path to virtualizing your data while keeping it secure but still well within your influence and reach.