Data virtualisation is not about IT – it’s about giving decision-makers immediate access to all the relevant information and only the relevant information. Information has become the strategic business advantage; hence how well businesses use the information at their disposal determines how well they perform in an increasingly competitive environment.

Simply owning vast amounts of data is not enough. To deliver business value, this data must be instantly accessible to the business decision-maker through a single access point, in formats that are easily understood. Data virtualisation delivers the solution. This agile data integration approach has matured over the last few years, and now allows organisations to gain more insight from their data, respond faster to ever changing analytics and BI needs and save 50-75% over traditional data replication and consolidation methods. Growing numbers of enterprises are seeing its advantages. Analysts Gartner, TDWI and the BI Leadership Forum have each estimated adoption at around 25% today, with projected growth to 50% within two years. In many cases, a move to data virtualisation begins with agile BI and analytics projects. In other instances, enterprises take a broader multi-project architecture approach to adoption. For example, a large energy company is using data virtualisation to provide a common data access approach to support all their upstream information requirements. Several investment banks are doing the same for their broker/dealer operations.

 However the data virtualisation journey may begin, the actual process of rolling it out follows a relatively simple series of events:
·  Step 1: Install – Data virtualisation’s easy-to-adopt middleware overlays existing infrastructure so enterprises start quickly and scale successfully.
·  Step 2: Develop – Data virtualisation provides rich data analysis, design and development tools to build the required business views (also known as data services).
·  Step 3: Run – When business users run a report or refresh a dashboard, data virtualisation’s high-performance query engine accesses the data sources and delivers the exact information requested.
·  Step 4: Manage – Data virtualisation’s management, monitoring, security and governance functions ensure security, reliability and scalability.

Business views provide instant access to the data that business users require, while shielding them from IT’s complexity.  It not only supports business growth and risk reduction, but also enables better operational management and technology optimisation. With time-to-solution being a critical factor in business today, data virtualisation should be an obvious investment.