Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility is the first book published on the topic of data virtualization.  In writing the book's foreword, well-known IT industry analyst Colin White of BI Research, summarizes data virtualization's history and value, concluding that data virtualization's time has come. This article includes excerpts from the book's foreword.

Supporting Business Users' Information Needs
Providing business users with the data they need to make effective decisions has always been difficult. Increasing data volumes, varieties of data and heterogeneous data stores are not making this task any easier.

For the past two decades, the solution to accessing disparate data has been to consolidate the data into a data warehouse, and provide users with tools to access and analyze this consolidated data.

Challenges to the Status Quo
However, growing demand to access data not managed by the data warehouse, coupled with the need to access current data for more agile decision making, means organizations have to change the way data is accessed and used by business users.

The solution is to give users a single interface to the data and data services they need, regardless of where the data is stored or how it is organized. This doesn't mean organizations have to abandon the data warehouse, but rather they need to extend it.

Data virtualization is a set of techniques and technologies that provide the key underpinnings that enable organizations to do this.

Data Virtualization Gains Momentum
Data virtualization is not new. It has been around for many years in a number of different guises, including enterprise information integration and data federation. It is only recently, however, that this approach has gained the recognition and success it deserves.

There are several reasons why data virtualization has taken so long to gain traction. Perhaps one of the biggest is that data virtualization was marketed initially as a way to build a "virtual" data warehouse and to avoid building a real, physical one. This approach was immediately assailed by data warehouse advocates as unusable and unworkable, and it took some time for data virtualization to recover from this assault and poor positioning.

Like any technology, it is important to understand where data virtualization can be used, and where it can't.

Beyond Data Warehousing
Another reason for the slow acceptance of data virtualization is that it was seen initially only as a technique for use in data warehousing.

As the case studies in Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility demonstrate, it has value for a wide range of enterprise data integration projects. This broad use is enabled not only by data virtualization's data integration capabilities, but also by its ability to act as a bridge to data supplied by middleware and services-based solutions.

For me, the feature of data virtualization that frequently goes unnoticed lies in its ability to provide IT and business users with a single high-level view of data that may be spread throughout the enterprise. This capability can dramatically simplify access to data for less experienced users.

Learn from Successful Organizations
Data virtualization is now a mature approach that has a wide range of uses, and what excites me about this book is the rich set of real-world case studies it contains. The proof of success of any technique or technology lies in its adoption, and these case studies will provide you with detailed information about how a wide range of different companies in a number of industries are achieving significant business benefits from the use of data virtualization.

Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility should be read not only by IT professionals who are interested in, or considering the use of data virtualization, but also by executives and business users who are looking for ways of improving access to data for business decision making.

- Colin White, BI Research

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