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Dealing with Unforeseen Events – How Data Virtualization Creates an Agile Environment

By January 21, 2014Article

Disruptive events such as rapidly evolving technologies, economic downturns and M&As have shifted the underlying forces of several industries and have led many businesses to make dramatic changes in how they operate. In fact, these unforeseen events have had a significant impact on specific business functions and have led companies to react with major changes in order to keep pace. Given the increase in the number and impact of such disruptive events, companies need a more proactive approach that includes developing business agility to better handle rapid changes. Unfortunately, the importance of building agility into a company’s IT infrastructure is often underestimated or overlooked, leading to an adverse impact on critical business functions. 

Business agility means not just managing changes in business processes and organizational structures but also building the agility in the underlying IT systems to enable the implementation of large projects in short time periods. To build this IT agility, companies are turning to the cloud, mobility, cheap Big Data processing power and increasingly to data virtualization to smooth out the turbulence of a disruptive organizational change. 

The impact from overlooking or underestimating the need to build agility into infrastructure is even more applicable in the event of a disruptive change as the success of business initiatives is often tied closely to how well the IT changes are managed. For example, post-merger initiatives designed to capture synergies are strongly related to IT. Examples include merging finance and HR systems, integrating customer data for cross-selling and vendor consolidation, etc. 

Even so, IT teams are given very little time to plan and execute these major system changes. Not only does this result in increased resource costs, it also creates delays and downtime on key operational processes.  

The example of the Delta-Northwest merger helps one understand the magnitude and complexity of these IT system changes. This merger was largely deemed a success, but it also required 2,000 employees to spend two years to analyze nearly 1,200 IT systems and to complete several projects including the migration of over 1.5 million passenger records from the Northwest reservation system to Delta’s system. 

So what does IT infrastructure agility entail?  

First, companies should be able to quickly add or remove source systems. One of the key IT projects after a merger is the consolidation of financial systems before the next quarterly reporting period. This requires adding several new data sources, yet the time available for integration tends to be fairly limited due to compliance reasons. 

Second, companies should be able to quickly build or modify data workflows in order to accommodate new data sources and data consumers. For example, one of the objectives of a merger may be to leverage the increased customer base to grow revenue, but companies spend months or even years analyzing and integrating customer data into their existing sales and marketing processes in order to realize the synergies.  

Finally, the users and the operational processes on the receiving end of the workflows should be decoupled from all underlying source systems and processes. This means that, after an acquisition, data consumers shouldn’t have to know or care which of the companies’ source systems the data is originating from and should be able to continue using current front-end tools. After all, call center personnel shouldn’t have to log in to a different application to field calls from customers of an acquired company. This information should be normalized and integrated into existing applications transparently. 

Data virtualization, which is a technology that enables a flexible, unified data layer, provides that solution for abstraction, decoupling and transparency of data across layers in the IT architecture. This in turn increases agility by providing a unified, normalized view of disparate data sources and enables real-time or scheduled delivery of this data to consuming users and applications such as reporting tools, operational processes, mobile and/or cloud apps.  

AAA of Northern California, Nevada and Utah (NCNU) recently underwent an enterprise-level restructuring process in which they split their 100-year-old company into separate insurance and auto services business units.  This required the auto services division or “auto club” to set up their own data center, migrate data and applications and build new integration workflows all while keeping reporting and other operational units like the call center functioning without disruption. 

To accomplish this, AAA NCNU deployed a data virtualization platform to serve as a buffer layer over their existing infrastructure, which they were sharing with both the insurance division and their upcoming new infrastructure. This helped to provide a normalized view of all source systems to the consuming users and applications so they could function as usual. At the data source level, data virtualization allowed them to make changes like adding new source systems and changing database systems to conform to their plans for the new architecture. 

As the migration process continued, the ability to quickly build virtual views within the data virtualization layer helped the company to reduce the development time needed to create integration workflows. For example, as AAA NCNU migrated membership data from legacy systems, they used the data virtualization platform to provide a unified view of their legacy and new member data systems in the format required by the downstream integration flows. This meant that the downstream processes didn’t have to be modified and that the project was completed faster and at a much lower cost.  

The unified data layer provided by the data virtualization platform also served as a layer of abstraction that masked all the underlying complexity due to data migration from the consuming users and processes. The result; AAA’s auto club was able to carry out a challenging migration project without any impact to customer facing applications and operational processes. 

A solutions architect from AAA NCNU summed it up best when he said, “Our business has a high appetite for change, but a low appetite for disruption.” 

In order for organizations to minimize impact from future disruptions, they should consider deploying a data virtualization platform as it behaves as “cartilage” to absorb shocks caused by sudden unforeseeable events. As in AAA’s case, the platform not only served to effectively manage change in the short term but also enabled the flexibility that prepares their IT infrastructure to weather changes in the long term. 

Suresh Chandrasekaran, senior VP, and Suhaas Kodagali, product marketing manager, at Denodo Technologies, a leader in data virtualization, collaborated to produce this article. For more information contact Suresh at





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