Information Strategy

A Smarter Approach to Information Integration

How data virtualization delivers seamless, on-demand access to information throughout the enterprise

It’s no surprise that data is growing. But with information sources ranging from RFID tags and smart meters to mobile phones, GPS-enabled devices, and social media, data growth isn’t just a volume issue anymore—it’s also a complexity issue.

In this environment, access to data is more important than ever before. Both business and technical users need the ability to explore, combine, and analyze large volumes of information from across and beyond the enterprise. Data virtualization offers an approach that enables easy access to information on demand.

 

Challenges and drivers of data virtualization

Although the modern era of computing offers many new opportunities, the business and IT challenges remain unchanged—and in some cases, magnified—due to the increasing demand for data. Several common pain points lead organizations to investigate data virtualization solutions as a data integration approach.

 

Slow implementation and adoption

While all integration approaches have the same goal—to effectively combine data from multiple sources and provide a unified view of that data—the time to delivery and ease of adoption for each may vary. A lengthy delivery cycle means the business must make do with the status quo until the solution is implemented. And if the solution is too complex, users will adopt it slowly or not at all—which means the IT department may not be able to recoup the cost of implementation.

 

Lack of common access and understanding of information

As the number of data sources and applications increases, organizations that fail to provide a common method for understanding and accessing all available information will find that the massive volume of data in their systems is essentially useless. Multiple information access points also increase the total cost of ownership since each access point requires administration, security, and management resources.

 

Source data complexity

From social media posts to machine data such as temperature readings and bar code scans, source data is becoming more complex and varied. Extracting and storing this data is no trivial task, but deriving insight from both structured and unstructured information is quickly becoming a requirement for maintaining a competitive edge. The complexity of the data sources is irrelevant to end users; all they need are answers to their questions. Organizations need an integration approach that can simplify data access and help boost productivity by making this complexity transparent.

 

Data virtualization delivers transparent, on-demand access to information

To address these challenges, organizations must make it simple for business users to leverage data confidently for any purpose. Data virtualization meets that goal.

Designed to provide easy access to information on demand, data virtualization focuses on simplifying access to data by isolating the details of storage and retrieval and making the process transparent to data consumers. By spreading data throughout an organization, data virtualization reduces the time required to take advantage of disparate data—making it easier for users to get the information they need and use the processes necessary to collect that information.

In general, there are two approaches of data virtualization. With data federation, data is virtually consolidated from multiple sources, making them appear as a single data source. IBM® InfoSphere® Federation Server and InfoSphere Classic Federation Server for z/OS® help with this approach. This method lets the end user access data anywhere in the enterprise, regardless of its format or vendor. The complexities that are typically associated with having to query data from multiple sources are hidden from the user; all that the user sees is the virtually consolidated data.

With data services, data is provided on demand to consumers regardless of where they’re located. InfoSphere Information Server for Data Integration helps with this approach. There is no need to know where the data is located or how to obtain it. In response to a data services request, the required data is retrieved and returned to the user. This level of transparency makes it extremely easy to access information that is spread across the enterprise.

 

Benefits of data virtualization

Data virtualization eliminates the need to move or duplicate data. As a result, organizations can use third-party data more easily, simplify compliance efforts, and reuse existing infrastructure more effectively. Data virtualization also delivers several other benefits for users across the enterprise.

 

Cost-efficiency

Because data virtualization involves virtual consolidation of data rather than physical movement, there is no need to create new databases or purchase additional hardware to store the consolidated data. This is a very attractive benefit for organizations looking for a cost-effective integration approach. In situations where physical data movement is not an option due to legal or compliance requirements or ownership issues—for example, when data is external to the organization—cost-effectiveness is an added bonus.

 

Low risk

All integration approaches yield considerable benefits, but solutions that require invasive IT changes often introduce risk. Data virtualization does not require additional hardware or IT infrastructure changes, so it is a very low-risk integration solution that fits seamlessly into an existing IT environment.

 

Complexity hidden to end users

With data virtualization, the complexity and disparateness of the data sources do not matter because those details are hidden. The end user will never know—and doesn’t need to know—the details about where the data originated. This means changes to source systems will not affect downstream applications. The burden on IT is reduced since the solution does not have to be reconfigured each time a change is made.

 

Fast adoption and time-to-value

Data virtualization helps to enable faster results by making information easily accessible to the enterprise. Building virtual data stores is much quicker than creating physical ones since data does not have to be physically moved. Because of its positive impact and fast time-to-value, a data virtualization solution usually gains widespread adoption and support quickly, leading to faster business results.

 

Conclusion

An effectively governed data virtualization solution with high-quality data provides a flexible and cost-effective approach for making data easier to access and use. As part of a broader information integration architecture, not only does this solution simplify the typically complex data landscape for end users, but it also helps power self-service initiatives by greatly increasing the accessibility of data within the entire organization.

IBM offers InfoSphere Federation Server and other information integration offerings to address all your requirements for federation, virtualization, and other approaches to integration information across the enterprise.

Has your organization explored data virtualization? Please share your experiences in the comments!

For more information on data virtualization, download the full-length IBM white paper on the topic here.
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Wendy Tam

Wendy Tam joined IBM through the DataMirror acquisition and is now part of the information integration product marketing and strategy group, focusing on data federation and virtualization.