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Turn Big Data Into Big Dollars

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Big Data can drive big dollars. For any growing business, that’s the bottom line. As the amount of information in the world grows, your enterprise needs to start turning these bytes into bank. One way to do that is to move Big Data to the cloud.

Research shows that a typical Fortune 1000 company that uses data 10 percent more effectively can generate $2 billion in additional revenue. In the consumer space, retailers can increase margins by 60 percent. Every enterprise must pay attention to Big Data.

What is Big Data?

Big Data is the collection and storage of massive amounts of data. IDC defines Big Data as projects collecting 100 terabytes of data, comprising two or more data formats. Big Data also refers to datasets so large that typical database software tools cannot properly capture, store, manage and analyze it. According to Garnter, there are three dimensions that create challenges and opportunities around Big Data: volume (amount of data), velocity (speed of data in and out) and variety (range of data types and sources).

Overall, Big Data is the continuous stream of digital information that arrives through many channels, including email, social media, mobile devices, system logs, customer or B2B transactions, and much more.

Big Data delivers a host of benefits, including productivity, higher revenues, better decision making and innovation. But the amount of data is growing at the astounding rate of 40 percent to 60 percent a year, and this flood of digital information can oftentimes be too big for an enterprise to handle with its current solutions. This presents some new challenges.

The Challenges

To generate useful insights, data must be acquired, stored and analyzed in thoughtful and cost-effective ways. However, there are challenges, including:

  • Existing infrastructure can’t handle Big Data: Because Big Data is less structured, traditional databases and analytics platforms cannot handle it. In fact, Big Data is unexplored terrain that will stretch and strain any company’s IT infrastructure.
  • Higher CapEx: Trying to handle Big Data without rethinking an existing on-premise infrastructure can result in the need to buy additional drives and servers to accommodate growing data, which can lead to sky-rocketing capital expenses.
  • Higher costs for non-strategic resources: The more servers and storage drives brought in-house, the more IT personnel is needed to tend to them.
  • Vendor lock-in that limits choices: When you’re locked into one vendor, you have to keep buying from them, even if you never see an acceptable ROI from their wares. You’re caught in a vicious cycle.

The Solution: Move Big Data to the Cloud…

One way to overcome these challenges and get more value out of Big Data is by moving it to the cloud. The cost-effective storage and pay-as-you-go model makes the cloud well-suited for Big Data. For example, consider a company that needs more computing resources to handle bursts of Big Data analytics on an unpredictable schedule. The cloud can provide a simple and affordable way to spin up as many extra servers as needed, release them as soon as the job is complete, and pay only for the time they were actually used.

Most CFOs consider the utility billing for cloud computing, paid out of operating budgets or OpEx, to be better for the corporate balance sheet. This means the cloud can provide the best of both worlds: better services plus a stronger bottom line.

According to Forrester researcher Holger Kisker using Big Data in the cloud makes sense for three key reasons:

  1. Big Data requires a spectrum of advanced technologies, skills, and investments. Do you really want this all in-house?
  2. Big Data includes huge amounts of external data. Does it make sense to move and manage all this data behind your firewall?
  3. Big Data needs a lot of data services. Why not focus on the value of your analysis, instead of simply managing your data?

For all these reasons, moving your Big Data projects to the cloud makes a lot of sense.

For more information on Big Data in the cloud, please check out the whitepaper “Turning Big Data Into Big Dollars.” And check out a recap of the Enterprise Cloud Forum webinar on how to turn big data into big dollars.

About the Author

This is a post written and contributed by Anand Bhadouria.

Anand is an Enterprise Solutions Architect with the Rackspace Advisory Services team. He is a strategic, business-oriented technology leader and enterprise cloud architect with over 19 years of experience. Anand has extensive global experience in application and IT infrastructure, consulting, outsourcing, pre-sales and project management. Anand received his Master of Science degree in Management and Engineering from the MIT Sloan School of Management and MIT College of Engineering where he focused on Technology Strategy, Innovation, Leadership and System Design Management. Anand has also spent some time at Harvard Business School specializing in Business Marketing and Competing with Business Models. In addition, Anand holds a Bachelor of Science degree in Information Technology from the University of Massachusetts, Lowell.


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2 Comments

Great read for any CxOs. Simple, concise and to the point remarks. I will suggest that besides pay as you go on storage side, big data processing costs can be lowered (by using cloud) drastically as majority of processing will be BI like work, which is usually periodic in nature (batch processing). Keep up the good work.

avatar Sarbjeet Johal on March 27, 2013 | Reply

I like the conciseness of this article. It is a great summary from the more profound whitepaper, tailor made for executives on the go and very didactical. Great work!

avatar Daniel Hernandez on March 27, 2013 | Reply

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