by Angela Guess
A recent article reports, “As every child knows, learning how to share toys with others is an important, but difficult to learn skill. The same is true for diverse groups within large enterprises, except instead of toys, data is the object of the sharing. Large enterprises learned long ago that effective sharing of data across lines of business was a critical success factor. But achieving this objective in large organizations has been especially complex due to: (1) Thousands of information consumers with varied roles and responsibilities; (2) A range of analysis and reporting applications addressing different business problems; (3) Multiple approaches to access, combine, and deliver data to these applications; and (4) Extreme data source volumes, variety, velocity and complexity. Traditional information architectures have not been agile enough to keep pace with today’s frenetic business change. Something has to give!”
The article continues, “Data virtualization combines SOA development principles including, decoupling, reuse, and agility with key information governance principles such as abstraction, shared semantic models and data standards. This combination enables organizations to build and deploy data services in a simpler, faster, more consistent manner that scales enterprise-wide.”
It goes on, “From the SOA or data services point of view, data virtualization provides: (1) Reusable Data Services – Each data service can e developed, deployed and modified as an independent, standalone component, providing greater flexibility and reusability. (2) Flexibility to Change Sources and Consumers – Data services loosely-couple the data sources and consumers, and therefore reduce the impact of changes at either source or consumer level. (3) Rapid Development to Increase Responsiveness – Data services can be developed and changed easily and rapidly using modern development tools, thereby providing the agility required in today’s fast-paced business world. (4) Componentized Services Simplify Development and Increase Flexibility – Data services can leverage one and other to split the work, for example across sourcing services, federation services, and standards transformation services to simplify development and provide even greater flexibility and reuse.”
photo credit: Lauren Manning
