Data Virtualization Going Beyond Traditional Data Integration to Achieve Business Agility eBook Judith R. Davis, Robert Eve
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This is a Book of Data Virtualization Case Studies
Data Virtualization Going Beyond Traditional Data Integration to Achieve Business Agility, the first book ever written on the topic of data virtualization, introduces the technology that enables data virtualization and presents ten real-world case studies that demonstrate the significant value and tangible business agility benefits that can be achieved through the implementation of data virtualization solutions.
This first chapter describes the book and introduces the relationship between data virtualization and business agility. The second chapter is a more thorough exploration of data virtualization technology. Topics include what is data virtualization, why use it, how it works and how enterprises typically adopt it. The third chapter addresses the many ways that data virtualization improves business agility, with particular focus on the three elements of business agility business decision agility, time-to-solution agility and resource agility.
The core of the book is a rich set of in-depth data virtualization case studies that describe how ten enterprises across a wide range of industries and domains have successfully adopted data virtualization to increase their business agility. The ten enterprises profiled are customers of Composite Software, Inc., a data virtualization software vendor.
These case studies are preceded by a summary chapter entitled Data Virtualization The User Perspective that synthesizes the business agility benefits achieved through data virtualization and provides a compendium of best practices for implementing data virtualization solutions. The summary is followed by the ten detailed case studies from Comcast, Compassion International, a Fortune 50 Computer Manufacturer, a Fortune 50 Financial Services Firm, a Global 50 Energy Company, a Global 100 Financial Services Firm, Northern Trust, NYSE Euronext, Pfizer and Qualcomm.
Each case study includes a complete and rich implementation profile that includes
- Organization Background. This section provides high-level context about the organization its industry, products, markets, revenues and more and a brief profile of the leader of the data virtualization initiative within the organization.
- The Business Problem. This section describes the specific business problem addressed by the data virtualization solution.
- The Data Virtualization Solution. This section describes how data virtualization was successfully deployed to fulfill the business needs described above. This includes information about the data virtualization platform and architecture, the consuming applications and data sources, and the deployment that successfully integrated these sources and consumers. Additional technologies, methodologies and strategies that contributed to the solution are also described.
- The Implementation Process. This section provides insights into the process used to implement the data virtualization solution. We also highlight implementation advice for others based on lessons learned.
- Summary of Benefits and Return on Investment. This section describes the enhanced agility and other business benefits as well as IT benefits realized from the adoption of data virtualization. Where possible, tangible ROI value is included.
- Summary of Critical Success Factors. This section identifies the features of the solution and implementation process that were most important to achieving success.
- Future Directions. Because data virtualization adoption can span multiple projects on the path to enterprise-wide deployment, this section identifies planned next steps as well as other factors to be considered in the near future.
In conclusion, the last chapter transforms earlier chapter insights into a concise set of data virtualization takeaways and guidance to encourage other organizations as they strive to achieve similar business agility success.
Data Virtualization Going Beyond Traditional Data Integration to Achieve Business Agility eBook Judith R. Davis, Robert Eve
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Data Virtualization Going Beyond Traditional Data Integration to Achieve Business Agility eBook Judith R. Davis, Robert Eve Reviews
This first book on the topic of data virtualization provides an excellent starting point for anybody trying to answer users' demands for an integrated view of the information needed to run and manage a modern business.
Data virtualization, in this and previous incarnations such as federation and EII, has long been a contentious topic for data warehousing. It's easy to see why data virtualization allows you to avoid consolidating and reconciling data into an enterprise data warehouse (EDW), which is usually the most complex and costly part of business intelligence (BI) projects. However, apart from some early marketing hype, data virtualization doesn't say you should use it instead of an EDW. And given the dramatic explosion in data volumes and varieties in recent years, together with business demands for instantaneous information access, the role of the EDW as sole provider of BI is open to question.
In BI and beyond, there is an emerging view that the operational and informational worlds must now be merged back together, not just in principle but in practice. Data virtualization offers agile solutions that enable this amalgamation. The real value of this book is that it confirms this view and demonstrates it in action in ten well-described case studies spanning a wide range of industries.
The only possible criticism is that all the case studies come from customers of one vendor, Composite Software - hardly surprising, given that Bob Eve, one of the authors, is EVP of Marketing there. However, the co-author is Judy Davis, an independent analyst who takes the broader view. The studies are written in a balanced and functionally oriented style that allows the reader to easily look beyond the product used to the business benefits and technological challenges being met. Extrapolation to another product set is thus straightforward.
Anyone contemplating data virtualization as a solution to their data integration needs, whether for BI or in a broader context, will benefit greatly from the clear thinking, existing experience and strong production values that have gone into this book.
It's easy to find books that tell you which technologies will be the "next big thing". To find a book that gives real-world examples of companies actually USING a technology is refreshing. This book does just that. Sure, you get an overview of what Data Virtualization actually is and why companies decide to use it, but a huge portion of this book is dedicated to example after detailed example of companies in many different industries utilizing the technology. It's hard to think someone could read this book and not be left with a clear idea of what Data Virtualization does, and how to apply it to their business should they chose to do so.
I found this book to be a very readable, practical introduction to Data Virtualization. Data Virtualization is one of the newer IT disciplines and a quick search on shows that not much has been written on it, yet. I think this book fills a gap in the industry.
The authors recognize Data Virtualization as an important tool in achieving enterprise agility. It must be considered as part of an overall strategy in achieving excellence. In our upcoming book, Business Intelligence Program we discuss the importance of agility in IT and BI in particular. Data Virtualization can be a component in implementing a successful, nimble strategy that meets the rapidly changing needs of the business.
As for the objection that the book is just an advertisement, I think it's written in a very straight-forward style. It definitely does not come across as a sales presentation. The list of companies which have lent their name and their success stories is impressive. I think the case studies only add credibility to the narrative.
If you're considering Data Virtualization, this is a must-read.
The challenges in accessing data continue to grow across the enterprise. Big Data, Cloud Data and highly regulated data all contribute to the problem and are forcing companies to reevaluate how they move, access or leverage this information. Innovation in the data integration space is critical for companies that are facing these issues. Data virtualization has found a place in this terrain and offers a unique solve to the problem. This book does an excellent job in delivering easy to understand examples and value propositions to support the technology. The focus on its agile benefits are accurate and help readers understand how/why this technology should be part of their data strategy. I like the real world case studies from companies such as Comcast, Northern Trust, Qualcomm, NYSE Euronext and Pfizer. The book is well suited for IT and Business executive who are exploring the topic and need to better understand the challenges and opportunities that data virtualization can deliver. The book isn't designed to act as a technical "how to" its intended to address the question of "why".
From a high level, the book describes data virtualization very well. After reading the book, I had a much better understanding. Only experience and pain will help you design, build and sell data virtualization.
This book provides a rather superficial look at a complex subject, data integration. It provides little in the way of guidance to help identify where data virtualization is applicable or feasible or how to solve challenges such as matching, linking and synchronizing heterogeneous data sets.
The case studies provide little detail of how these organizations addressed real world problems such as lack of data standards and data quality.
The book is a commercial for a data virtualization product.
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