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Big Data and the Analytical Enterprise

Big Data and the Analytical Enterprise

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At the recent Davos Summit, Big Data was described as an asset as valuable as currency or gold. Why this sudden excitement over something that has been around for years? Because the tools are now available for organizations to build a more powerful Analytical Enterprise – one that turns Big Data from a problem to a solution.

What is Big Data?

The growth in data, digital data, has become exponential. Every day, we create 2.5 quintillion bytes of data. 90% of the data has been created in the last two years alone. This data comes from everywhere: from sensors used to gather climate information, posts to social media sites, digital pictures and videos posted online, transaction records of online purchases, and from cell phone GPS signals and electronic markets to name just a few. 

IDC estimates point to it doubling every other year.

This highly varied data, flowing faster and growing larger than ever before, is “Big Data”.

The tools to manage Big Data can be thought of in three parts:

  • Consolidation and aggregation – the assembly of data
  • Storage and analysis – the ability to access and analyze data
  • Absorption – presenting data so it can be easily consumed and meaningful insight obtained.

Conceived in this way, Big Data technologies involve a platform approach from the creation of data to its final consumption. Self-service BI is an important part of the Big Data story. Data is useless if you can’t do anything with it.

What defines an Analytical Enterprise?

An enterprise that uses data to understand their customers, risk and operations more completely, redefining their business opportunity as a result, we call an analytical enterprise.

The value of Big Data lies in the fact that it offers businesses the opportunity to see everything and miss nothing. The technology of Big Data allows us to store and compute practically anything for the first time in history. The impact can drive significant increases in value across many industries including financial services. Customer segmentation and targeting, risk management, investment management, compliance and financial reporting; even managing the enterprise becomes easier when we have access to more, perhaps unlimited information.

One great example is from a large insurance company. By using sensor technology in cars to monitor driving behavior, and a Big Data platform to analyze the output, they can more finely price insurance risk. By taking a more granular approach they can outperform their competitors on price and portfolio quality.

Big Data is the challenge - Creating the analytical enterprise is the solution.

The true analytical enterprise is one that takes a holistic view of its data platforms and an end-to-end approach to data management. It has the ability to see the wood and the trees, viewing everything in context. With both a laser focus on detail and a landscape view of the organization, an Analytical Enterprise can see its risks and its rewards, giving it the upper hand amongst its peers.

 

For more information...

To support this mining of Big Data, a slew of new technologies has arisen. The most talked about is Hadoop. But what exactly is Hadoop? How should enterprises leverage it? And how should they not..?

  • David,

    This blog post is spot on. I appreciate the differences you highlighted between Big Data -- the raw information, and an Analytical Enterprise-- transforming that raw data into insight. We wrote a blog post on how Big Data affects financial organizations and highlighted specific source on where to find insight.

    Let us know what you think. We would appreciate your input.

    www.lattice-engines.com/.../prospecting-for-business-banking-a-new-world-part-1

    Alicia Brayboy

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