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Article

Now's the Time to Take the Leap into Data Virtualization

Data virtualization for small and mid-sized organizations

Financial services IT generally leads any new technology wave.

Large telecoms, pharmaceuticals, and energy firms follow quickly, with retail, government and smaller enterprises typically adopting as new technologies move to mainstream.

Given that data virtualization has now reached mainstream, how is small and mid-sized organization adoption of data virtualization proceeding?  And how are these firms benefiting?

What Is Data Virtualization?
Data virtualization is a data integration approach and technology organizations use to provide users with a business view of data, improve business agility and reduce IT costs.

Data virtualization technology is a form of data integration middleware that leverages high-performance software and an advanced computing architecture to provide business information from multiple sources in a loosely coupled, logically-federated manner.

Most business applications, including BI, analytics and transaction systems, can access data through the data virtualization layer.  This consumption is on demand from the original data sources, including transaction systems, operational data stores, data warehouses and marts, big data, external data sources and more.

Key enabling technology includes:

  • Business views of data using logical data models that provide complete, high quality, actionable information.
  • High performance query algorithms and other optimization techniques that ensure timely, up-to-the-minute data delivery.
  • Standard APIs and an open architecture that simplify consumer-to-middleware-to-data source connectivity.

How Is Data Virtualization Different?
For the past two decades, the solution to accessing disparate data has been to consolidate the data, generally into a data warehouse and associated data marts.

By implementing a virtual data integration layer between data consumers and existing data sources, an organization greatly reduces their physical data consolidation and replicated data storage needs.

When compared to data-warehouse-centric integration approaches, data virtualization enables organizations to accelerate delivery of new and revised business solutions while also reducing initial and ongoing solution costs.

Because data virtualization delivers the flexibility and agility that the traditional approaches were never designed to do, IT groups are adopting data virtualization to complement their earlier data warehouse and ETL investments.

How Does Data Virtualization Improve BI Agility?
That is a very important question to ask.  And we wrote an entire book entitled Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility to answer it.

In the book, we analyzed data virtualization adoption at ten organizations. Business agility - improving their ability to quickly take advantage of new or changing business opportunities - was the key benefit each achieved from data virtualization.

These organizations found data virtualization addressed three elements of business agility:  business decision agility, time-to-solution agility and resource agility.

For business decision agility, data virtualization helped provide the knowledge and insight that could only be derived from complete, high-quality and actionable information.

Data virtualization's streamlined approach to data integration, iterative development process and ease of change significantly improved time-to-solution agility. Using data virtualization these IT groups were able to more quickly develop and deliver the information necessary to support new analyses and decision-making processes.

Data virtualization also provided greater resource agility through superior developer productivity, lower infrastructure costs and better optimization of data integration solutions.  With IT operations are one of the largest ongoing resource expenses and IT infrastructure is one of the largest capital expenditures, these resource agility gains were substantial, millions of dollars per year at larger enterprises such as the NYSE and Qualcomm.

Is Data Virtualization Only for Large Enterprises?
In general, large enterprises tend to be early adopters for all new technologies.  For example, they were the first to deploy data warehouses fifteen years ago, data warehouse appliances five years ago, and NoSQL data stores today.  In many instances, they adopted data virtualization to help them extend and gain more value from these earlier investments.

Further, larger enterprises have more silos of data.  And thus they can more easily justify new data integration investments.

That said, the good news is data virtualization works equally well for smaller enterprises or at the project level in a large enterprise.

And the further good news is that larger enterprises' earlier investments are now paying off in stronger data virtualization offerings from everyone - small, medium or large.

Small and Medium Enterprise Adoption Is Accelerating
At Composite Software, we have a number of small and medium enterprise customers.  Let me talk about just a few.

The first is a non-profit, Compassion International.  They provide charitable support services to children in developing countries such as Haiti where poverty is a huge problem.  By 2020, the organization wants to quadruple the number of its beneficiaries.  To achieve this goal, the IT team needed to modernize the organization's information infrastructure.

Data virtualization has enabled Compassion to both scale their BI infrastructure and meet demanding new information requirements much more easily and quickly than before.  Time-to-solution for new information requests has improved by more than 50%.  And data quality and integrity have improved as well.

Is Now the Time?
Other small and mid-sized data virtualization adopters include Brown University, Carfax, Cricket Wireless, IEEE, Kaplan, Massachusetts Department of Education, Partnerships for Schools, Scripps Networks and many more.

Like the larger enterprises, these organizations and numerous other small and medium-sized enterprises share substantive business pressures and face significant technology transformations.

In every case, they were willing to look beyond traditional data integration methods and try something new, data virtualization.   And as a result, all are seeing significant business decision, time-to-solution and resource agility benefits.

You can too!

More Stories By Robert Eve

Robert Eve is the EVP of Marketing at Composite Software, the data virtualization gold standard and co-author of Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility. Bob's experience includes executive level roles at leading enterprise software companies such as Mercury Interactive, PeopleSoft, and Oracle. Bob holds a Masters of Science from the Massachusetts Institute of Technology and a Bachelor of Science from the University of California at Berkeley.