The Data Virtualization Gold Standard

Robert Eve

Subscribe to Robert Eve: eMailAlertsEmail Alerts
Get Robert Eve: homepageHomepage mobileMobile rssRSS facebookFacebook twitterTwitter linkedinLinkedIn


Related Topics: Virtualization Magazine, Desktop Virtualization Journal, SOA & WOA Magazine

Article

Why Bother to Abstract Your Data?

An important SOA concept comes to life with data virtualization

The benefits of providing the business side of the house with better access to information assets are many.

But so too are the integration challenges that IT must address.

Is there a better way?

Consider data abstraction, a concept well understood by SOA architects that has recently gained favor with information architects within an overall data virtualization strategy.

IT Complexity Reigns
Consider the information landscape in a typical large enterprise.  It includes:

  • Large volumes of complex, diverse data
  • A wide landscape of application silos and fit-for-purpose data stores
  • Each data source has its own schema and syntax
  • Few sources are structured properly for consumption by other applications
  • Many sources are incomplete, duplicated - or both
  • And new sources, middleware and consumers are added at a relentless pace.

Little wonder that IT has a huge backlog.

Data Abstraction Has Many Benefits
In the context of these many information challenges, data abstraction can provide a number of key business and IT benefits.

  • Deliver new business information sooner - The time required to fulfill new information needs can be shortened because data abstraction lets application developers understand new data sources more quickly.
  • Align business and IT models - Hiding data complexity, structure and location issues within its logical business or canonical models, data abstraction can improve specification and solution delivery, while cutting solution development time and costs.
  • Insulate business and IT changes - Data abstraction insulates consuming applications from source changes and insulates data sources from changing consuming applications. Developers are free to build their applications using more stable data views and services. This also allows ongoing changes and relocation of physical data sources without impacting consumers.
  • End-to-end governance and control. Developers, modelers, database administrators, data stewards and more can align themselves around a common data abstraction approach and unified schema, from source to consumer.
  • More secure data. Data security methods and controls are applied consistently across all abstracted data sources and consumers.

Moving from Why Data Abstraction to How Data Abstraction
If you agree that data abstraction provides many benefits, how can an enterprise ensure a successful data abstraction implementation?

Step one is to select a data virtualization platform on which you can develop, deploy and manage your data abstraction activities.  Take a look at How Enterprises Measure Data Virtualization Platform Maturity to better understand the critical evaluation criteria. Once you understand the key features, take a look at the Composite Software Data Virtualization Platform to see how these features are implemented by one of the leading data virtualization providers.

To help justify your data virtualization platform investment, take a look at How to Justify Data Virtualization Investments which provides a nice summary of virtualization's business and IT value propositions.

People and Process Are Important Too!
Once you have the technology selected, the next step is to address the people and processes that bring data abstraction to life.  Data modeling is a key process activity.  And the way you model data for data abstraction is quite different than the models and schemas typically associated with building data warehouses for BI or integrating business processes within a service-oriented architecture.  Think layers within the data virtualization layer, for example a mapping layer, a business view layer, a formatting layer and a physical layer.

My colleague Mike Tinius provides tremendously well summarized "how" insights in his recent Information Management article entitled Roles and Reference Architecture for Data Abstraction Success: Information complexity forces data abstraction. For more depth here, the Composite Data Abstraction Best Practices white paper provides a number of addtional data abstraction modeling coaching tips.

Just Do It!
Once you have why and how figured out, just do it!

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.