COLUMBUS, OH, April 09, 2013 /24-7PressRelease/
-- With Big Data making headlines daily, it's easy to mistake "lots of data" for "Big Data." As most IT folks agree, organizations of all stripes, from government agencies to academia, have been dealing with massive data sets for years. "But just because you have a lot of data, that doesn't mean it should be considered 'Big Data,'" says Jim Gallo, National Director of Business Analytics at ICC, a leader in business technology solutions focusing on big data and application development
"If an organization has large volumes of structured data -- point-of-sale data, inventory data, sensor data -- that doesn't translate directly to a Big Data problem or opportunity," says Gallo.
Today, most organizations use data warehouses and business intelligence (BI) suites to meet their analytics needs. But BI suites are limited to analyzing structured data in relational databases. When you combine the three "Vs" of Big Data -- volume, variety and velocity -- with unstructured data such as YouTube videos or medical images with the desire to learn something new from those mashups, you enter Big Data territory, according to Gallo.
"When you want to do something other than store and fetch images; when you begin to look inside the images and draw correlations to other data types like electronic health records (EHRs) or a Twitter feed or weather data, that's when you have a Big Data challenge," says Gallo.
Three Ways to Know if Your Challenge is Big Data or Lots of Data
So how can an organization know if the challenge it is facing is Big Data or just lots of data?
1. Are you learning new things? When you are interested in learning new things from your existing data by putting them into an analytics platform and combining it with other unstructured data sets so you can find cause and effect, then you are dealing with a Big Data challenge. But, if you are simply retrieving and storing large files without the need to combine them with other information or conduct analytics on them, then you're likely facing a "lots of data" challenge.
2. Is your data time-dependent? Another "tell" is if the information you want to analyze is streaming by at high velocities and the value of that information is time dependent. High frequency trading (HFT) is a good example of time dependent data analyzed in real time so Wall Street traders can make money. HFT algorithms can be written to incorporate myriad factors, such as currency fluctuations, political decisions or Federal Reserve actions, with current news headlines, to affect trades. Those trades make or lose money based on timing the stock market to the millisecond.
"Suddenly you're correlating more variables that were historically unstructured in nature," says Gallo. "It's all about timing and the organization that builds the best algorithms -- that consider the most variables and have the highest degree of predictability -- wins."
3. Are you combining your data streams? Single feed data streams that relay one type of event, such as a cash register sale sent to a back-end inventory control and ordering system, is a typical type of data collection. A big box retailer may operate tens of thousands of terminals together streaming hundreds of thousands of simultaneous data feeds into the same database. This is not Big Data because those feeds simply initiate predetermined actions like ordering more inventory or shipping items now.
But when those same data feeds are combined with other data streams, like the price of fuel at a logistics company to optimize shipping costs, then it becomes an example of a Big Data challenge.
"The BI tools exist to deal with individual steams of data," says Gallo. "But when you bring in the variety and the volume -- millions of transactions per hour for example -- and consider other data types, that makes it Big Data."
- Want to learn more about Big Data and how to get started? Download an ICC White Paper: Five Practical Questions for Starting a Big Data Initiative at http://bit.ly/icc-resources
ICC, based in Columbus, Ohio, is a leading provider of enterprise technology solutions. With a staff over 500 highly trained consultants, we are experts in Strategy, User Experience, Visual Design, Engineering, Project Management, Business Analytics and Quality Assurance. Using these skills, we develop and deploy innovative, business-critical solutions that enable Fortune 500 and mid-market organizations to improve operational efficiencies. Our Business, Digital and Technology solutions give our clients a competitive advantage that helps them drive revenues and increase margin.
ICC is a Microsoft Gold Certified Partner and an IBM Premier Business Partner. Clients include Nationwide, Cardinal Health, McGraw Hill, the State of Ohio, and Honda.
ICC is committed to serving its clients, community and country by developing U.S.-based leaders who work hard to strengthen the American economy. More information is available at http://www.icctechnology.com
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