The Data Virtualization Gold Standard

Robert Eve

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Ready, Set, Go! Get Started on Data Virtualization

Data virtualization adoption follows a well-known path

So you like what you have heard about data virtualization.

Who can argue with the business decision, time-to-solution and resource agility benefits that arise from data virtualization success?

But as with any new technology, you know you need to begin your data virtualization adoption journey with a business justification and a technical evaluation, before you can commence a phased implementation.

Business Justification Is the First Step
The business value of data virtualization comes from its ability to help organizations deliver complete, high-quality and actionable information more quickly and with fewer resources than traditional data integration approaches.  This faster time-to-solution advantage translates into faster realization of the business benefits - e.g., increased revenue, improved customer service and retention, enhanced competitive responsiveness and better regulatory compliance - that are the business drivers behind new information requests.

An example is the best way to understand why benefits are realized faster with data virtualization.  Let's assume the business wants to implement an enhanced customer self-service portal in order to improve customer satisfaction. This initiative is financially justified based on the expectation that it will generate one million dollars in additional revenue per month. If the use of data virtualization would result in a three-month shorter time to solution than an alternative data integration approach, then an additional three million dollars would be generated.

Additional benefits would include initial IT development resource savings from the faster development time and long-run infrastructure cost avoidance due to reduced data duplication.  This combination of hard and soft savings could then be used to justify the purchase of data virtualization technology.

In-depth Technical Evaluation Follows
Once the business case is clear, a thorough technical evaluation of alternative data virtualization offerings is often the next step in the process of adoption.  IT organizations typically have standard methodologies for identifying a set of viable technology vendors, refining it to a short list for detailed evaluation and then performing deep dive proofs of concept and "bake-offs" that result in the selection and purchase of an appropriate data virtualization technology offering.

Phased Adoption Is a Best Practice
As described my recent article, What Is Your Strategy for Data Virtualization?, once a data virtualization technology has been purchased, most organizations initially deploy data virtualization on a subset of possible data integration projects, functional groups and/or information domains using one of the five typical usage patterns.  An example is BI data federation for research and development.

This allows the organization to concentrate expertise and thus be more effective in its initial use of data virtualization technology.  From this foundation, within a year or two, deployments typically expand to more use cases across more domains and groups, eventually resulting in enterprise-scale deployment.

In many large enterprises, a BI or Integration Competency Center (ICC) is often the home for enterprise-wide scale-out of technology such as data virtualization.  ICCs combine and evolve the people, processes and technologies required to maximize both business and IT benefits.

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.