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Illustration Of The Cloud Analytics Reference Architecture (Graphic: Booz Allen Hamilton)

Booz Allen Hamilton today released “Delivering on the Promise of Big Data and the Cloud” and “Developing a Business Case for Cloud: Analyzing Return on Investment for Cloud Alternatives May Yield Surprising Results,” two perspectives in its new Concepts in the Cloud series.

By 2020, the amount of information in the U.S. economy is expected to grow by 44 times – and yet executives admit they are unprepared to take full advantage of big data and cloud computing. Concepts in the Cloud draws from Booz Allen’s work helping private and public sector organizations move beyond traditional techniques that stovepipe data to new, more holistic ways of viewing data that unlock business-driving insights.

“Booz Allen’s approach to the cloud – whether it be how we draw the greatest value from data, or how we evaluate the business case – was developed as a result of ongoing collaboration with the U.S. government and constantly evolves and adapts as we uncover new trends and insights in big data,” said Booz Allen executive vice president Mark Herman. “Our Concepts in the Cloud series will help senior leaders understand this and the holistic approach that’s needed to derive the greatest value from the influx of data – to move to that highest level of advanced analytics.”

Unlock New Insights: About “Delivering on the Promise of Big Data and the Cloud”

To open up the tremendous potential buried in the avalanche of data, Booz Allen has developed the Cloud Analytics Reference Architecture. Today, organizations are forced to make decisions based on limited access to information. But this approach – rooted in a mindset change – opens new avenues for analytics that lead to critical, mission-enabling insights.

The Cloud Analytics Reference Architecture consolidates previously-siloed data into a manageable, useful, common pool, or “data lake.”

By removing constraints of conventional techniques that lock data and analytics into stovepipes, analysts can ask more intuitive questions, search for unexpected data patterns and focus more on human insight and action. The Architecture:

  • Removes the constraints created by data siloes
  • Allows organizations to “experiment” more with the data, and to ask more intuitive questions
  • Enables people to focus on creating value by letting computers take over much of the work done now
  • Ensures subject matter experts can explore the data

Look before You Leap: About “Delivering on the Promise of Big Data and the Cloud”

Understanding the true business case of transitioning to the cloud requires paying careful attention to cost, productivity benefits and return on investment. A rigorous, systematic analysis of the return on investment of cloud solutions before signing on to a preferred system will give agency leaders a clearer picture of the costs and benefits of moving to the cloud. In fact, a move based on cost savings alone rarely yields a positive return on investment. This analysis must cover:

  • Cost considerations: these transition costs include how quickly agencies can close out legacy architecture and shift software and applications, as well as the extent to which data storage facilities and the IT workforce can be repurposed or retrained once the cloud has been introduced.
  • Potential productivity benefits: productivity gains across disparate activities can be difficult to pin down, and even tougher to ascribe to a single investment. Including the potential for productivity gains in a calculation of return on investment begins with a study of current costs, analyzing whether or how those costs can be permanently reduced once in-house data management is replaced by a cloud system.

The biggest benefit of moving to the cloud comes from creating efficiencies within the organization once data is more universally and readily accessible. Rich rewards are available when leaders study the business case upfront; down the line, organizations will enjoy meaningful productivity gains as the cloud helps to reorganize work processes.

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