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Why Your Business Will Value Data Virtualization

Data virtualization from the business point of view

Access to and analysis of complete, high-quality actionable information is the key to effective business decisions making.

Data virtualization enables IT to provide business with the information it needs with greater agility and lower costs than traditional data integration approaches and technologies.   As a result, business units in every industry are pushing on IT to adopt data virtualization.

  • How does data virtualization apply to your organization?
  • How will you meet your industry-specific data virtualization needs?
  • Will your data virtualization investments pay off?

Data Virtualization Adoption Strategies
In What Is Your Strategy for Data Virtualization?, five data integration challenges that data virtualization was capable of solving were identified.  Understanding these challenges and solutions can help guide an enterprise's data virtualization adoption strategy in general.

And while the above challenges apply in every industry to some degree, data virtualization adoption varies from industry to industry.  Data virtualization industry solutions help both Business and IT to better understand how data virtualization will work in their organization. Below are examples from Communications, Energy, Financial Services and the US Federal Government.

Data Virtualization in Communications
Why Communications and Media Companies Like Data Virtualization
identified how communications and media companies, such as AT&T, Bell Canada, Comcast, CondeNast, Level 3, Nielsen, Scripps Networks, TELUS, Time Warner Cable and TurkCell rely on the data virtualization platforms to provide the dynamic and diverse information required across a range of strategic initiatives and business-critical IT projects.  These include the following, just to name a few:

  • Flexible Ratings Data Analytics - To enable their TV network customers to respond faster to viewing trends via more robust ratings analysis, this marketing information company used data virtualization.  Results included a 50% faster response to new data requests, 80% faster reporting runtimes, improved customer satisfaction and 250% payback in nine months.
  • Media Access and Ad Sales Reporting - To improve sales teams' productivity, this lifestyle cable media company used Composite Software's data virtualization platform to combine data from disparate media access and ad sales management systems. Results included a 2% increase in ad sales with payback in four months.
  • 360° View of Cellular Customer Data - To maximize revenue per customer and customer service levels, this European mobile phone operator used Composite Software data virtualization products to combine customer service data from their customer reporting data warehouse, billing data from their financial systems, and call and configuration data from their operational support systems to deliver a 360o view of customers to their customer service representatives.  Faster issue resolution and more productive up-sell programs reduce churn and increase revenues.

Data Virtualization in Energy Companies
Why Energy Companies Like Data Virtualization
identified how four of the top five global energy companies rely on data virtualization to provide the diverse information that fuels upstream, downstream and back-office business success  Here are but a few of the use cases these innovative IT organizations have deployed:

  • Well Maintenance and Repair - Keeping wells up and pumping drives revenue. When wells go down, getting the right repair rigs and teams on site fast is critical. To allocate these scarce resources optimally requires dispatchers and triage teams have real-time access to repair rig status, staffing availability, best practice procedures, maintenance records, flow rates, and more.  Data virtualization accesses and combines this diverse data so the oil and gas keep flowing.
  • Regulatory Reporting - The energy industry is one of the most highly regulated industries today. EPA, OSHA, DOT, and many other federal and state agencies require hundreds of compliance reports.  Because internal systems have been optimized for operations, not compliance, integrating the data needed from across these systems is often the biggest component in your compliance reporting costs.  Data virtualization quickly and easily federates diverse data from across operational systems, while leaving operating data in place to avoid the extra costs that result from unnecessary data replication.
  • Research and Development - Effective R&D pipeline management is the key to expanding energy sources, enhancing recovery and yield, and reducing costs in the energy business.  Currently, most research project information resides is multiple systems.  Managers have to access these separate systems to extract, compile, and assemble reports from multiple laboratory operations in order to keep up. Data virtualization offers easier access and visibility across the entire R&D process.

Data Virtualization in Federal Agencies
Why Federal Government IT Leaders Like Data Virtualization
identified how with money tighter than ever, federal agencies are under increasing pressure to improve efficiency, share information more readily and execute on ever-expanding congressional mandates.  This has led to a proliferation of data virtualization adoption across multiple agencies to provide solutions such as:

  • Federal Enterprise Architecture (FEA) Model Support - Data services built and deployed using data virtualization are key enablers for the following FEA components; Service Component Reference Model, Technical Reference Model, and Data Reference Model.
  • Cross-agency Data Sharing - Data virtualization can help the government share data held in disparate IT systems and groups, presenting the information to multiple agency applications in a uniform fashion.
  • Operational Improvement - By providing on-demand capture and analysis of operational data, data virtualization helps government agencies make better decisions and improve operations.

Data Virtualization in Financial Services
Why the Financial Services Industry Likes Data Virtualization
highlighted several of the most frequent use cases that have made the Financial Services industry, the largest adopter of data virtualization to date including:

  • Risk Management - Data virtualization aggregates a single view of institution-wide risk so you can better manage market, credit and operational risks in real-time.
  • Reference Data Sharing - Data virtualization provides a single virtual source for reference and other data required to complete a financial transaction or a critical analysis.
  • Prime Brokerage Reporting - Data virtualization provides the single view of positions and trades your prime customers' want, whenever they want it.
  • Mergers & Acquisitions - Data virtualization lets you virtually federate data from across these duplicate systems so you can gain cross-selling synergies sooner.
  • Compliance Reporting - Data virtualization simplifies compliance reporting for regulatory initiatives including Dodd-Frank, Basel II and Sarbanes-Oxley.  Because internal systems have been optimized for operations, not compliance, data virtualization reduces the data integration component in your compliance reporting costs.

Data Virtualization ROI
Compelling financial return is critical for any IT investment today.  IT business cases must demonstrate value through tangible business and IT metrics that align with the strategic objectives of the business units that they serve.

Not only must this value be proven, it must be proven early in the acquisition process to justify technology evaluation efforts and then re-proven again after implementation to justify expanded adoption

How to Justify Data Virtualization Investments identified five key data virtualization value drivers for business and IT.  These include:

  • Sales Growth
  • Risk Reduction
  • Time Savings
  • Technology Savings
  • Staff Savings

For more in-depth tools that can help you calculate these benefits, my company, Composite Software, provides a Data Virtualization Value Framework.

More Stories By Robert Eve

Robert Eve is the EVP of Marketing at Composite Software, the data virtualization gold standard and co-author of Data Virtualization: Going Beyond Traditional Data Integration to Achieve Business Agility. Bob's experience includes executive level roles at leading enterprise software companies such as Mercury Interactive, PeopleSoft, and Oracle. Bob holds a Masters of Science from the Massachusetts Institute of Technology and a Bachelor of Science from the University of California at Berkeley.

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Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a multi-faceted approach of strategy and enterprise business development. Andrew graduated from Loyola University in Maryland and University of Auckland with degrees in economics and international finance.
Wooed by the promise of faster innovation, lower TCO, and greater agility, businesses of every shape and size have embraced the cloud at every layer of the IT stack – from apps to file sharing to infrastructure. The typical organization currently uses more than a dozen sanctioned cloud apps and will shift more than half of all workloads to the cloud by 2018. Such cloud investments have delivered measurable benefits. But they’ve also resulted in some unintended side-effects: complexity and risk. End users now struggle to navigate multiple environments with varying degrees of performance. Companies are unclear on the security of their data and network access. And IT squads are overwhelmed trying to monitor and manage it all.
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Evan Kirstel is an internationally recognized thought leader and social media influencer in IoT (#1 in 2017), Cloud, Data Security (2016), Health Tech (#9 in 2017), Digital Health (#6 in 2016), B2B Marketing (#5 in 2015), AI, Smart Home, Digital (2017), IIoT (#1 in 2017) and Telecom/Wireless/5G. His connections are a "Who's Who" in these technologies, He is in the top 10 most mentioned/re-tweeted by CMOs and CIOs (2016) and have been recently named 5th most influential B2B marketeer in the US. His social media "Klout"​ score is 81 and rising!