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5/7/2014
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5 Big Data Use Cases To Watch

Here's how companies are turning big data into decision-making power on customers, security, and more.

sitting in their customers' environment, and they phone home with information about the use, health, or security of the device," said Gallivan.

Storage manufacturer NetApp, for instance, uses Pentaho software to collect and organize "tens of millions of messages a week" that arrive from NetApp devices deployed at its customers' sites. This unstructured machine data is then structured, put into Hadoop, and then pulled out for analysis by NetApp.

3. Data warehouse optimization
This is an "IT-efficiency play," Gallivan said. A large company, hoping to boost the efficiency of its enterprise data warehouse, will look for unstructured or "active" archive data that might be stored more cost effectively on a Hadoop platform. "We help customers determine what data is better suited for a lower-cost computing platform."

4. Big data service refinery
This means using big-data technologies to break down silos across data stores and sources to increase corporate efficiency.

A large global financial institution, for instance, wanted to move from next-day to same-day balance reporting for its corporate banking customers. It brought in Pentaho to take data from multiple sources, process and store it in Hadoop, and then pull it out again. This allowed the bank's marketing department to examine the data "more on an intra-day than a longer-frequency basis," Gallivan told us.

"It was about driving an efficiency gain that they couldn't get with their existing relational data infrastructure. They needed big-data technologies to collect this information and change the business process."

5. Information security
This last use case involves large enterprises with sophisticated information security architectures, as well as security vendors looking for more efficient ways to store petabytes of event or machine data. In the past, these companies would store this information in relational databases. "These traditional systems weren't scaling, both from a performance and cost standpoint," said Gallivan, adding that Hadoop is a better option for storing machine data.

When it comes to managing data, don't look at backup and archiving systems as burdens and cost centers. A well designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems. Read our The Agile Archive report today. (Free registration required.)

Jeff Bertolucci is a technology journalist in Los Angeles who writes mostly for Kiplinger's Personal Finance, The Saturday Evening Post, and InformationWeek. View Full Bio

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KKring
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KKring,
User Rank: Apprentice
5/10/2014 | 1:19:08 AM
Big Data is great, but many don't know what to do with it
Big Data is great.  But so many don't know how to fully leverage it.  How does all of the data fit together?

One challenge is that most business schools, teach business in silos. Marketing, finance and operational silos. Once you get to their graduate programs, they teach in deeper versions of each silo. Business silos are great, for the efficiencies they bring. You can't get those efficiencies any other way. But business cuts across silos to get actual work done. 

What we should do is teach the collectors of data, the analyzers of data and the end users of data how it all fits together.  When you know how it all fits together, you are better able to determine how to best utilize your resources.  Without knowing how it all fits together, you are left with a disjointed series of data points that can confound people and at its worst, damage the company by making decisions based on an incomplete picture of what is going on.

https://www.linkedin.com/today/post/article/20140426140918-7115569-big-data-great-now-what-do-we-do-with-it
HM
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HM,
User Rank: Strategist
5/8/2014 | 2:15:58 PM
HPCC
Jeff, very insightful Big Data article. Many uses of big data have a measurable positive impact on outcomes and productivity. Areas such as record linkage, graph analytics, deep learning and machine learning have demonstrated being critical to help fight crime, reduce fraud, waste and abuse in the tax and healthcare systems, combat identity theft and fraud, and many other aspects that help society as a whole. It is worth mentioning the HPCC Systems open source offering which provides a single platform that is easy to install, manage and code. Their built-in analytics libraries for Machine Learning and integration tools with Pentaho for great BI capabilities make it easy for users to analyze Big Data. Their free online introductory courses allow for students, academia and other developers to quickly get started. For more info visit: hpccsystems.com
6 Tools to Protect Big Data
6 Tools to Protect Big Data
Most IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
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