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Sunday, April 13, 2014

Big Data Analytics

BY:  Jared Grimes

            What is Big Data? Everyone does not have the same consensus of the term, but the most accurate definition of big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.  Its purpose is to take a large variety of data to uncover unknown correlations, hidden patterns, and other beneficial information.   Traditional data collection is just as important for the process as the digital sources used. The main goal of Big Data is to vastly assist companies in their decision making process.

            How does it work? Data scientists analyze massive volumes of transaction data as well as other data sources that may be left out by conventional business intelligence programs. Some of the other data sources may include Web server logs and Internet clickstream data, social media activity reports, mobile-phone call detail records and information captured by sensors.  Big data analytics uses similar software tools used as part data mining.  Often times the unstructured data sources used for big data will not fit in more traditional data warehouses.  These warehouses also are not able to handle the processing demands posed by big data.
            New technology is being launched, like Google’s BigQuery to increase companies’ efficiencies.  Unlike its competitors, such as the services provided by Amazon Kinesis, BigQuery allows developers to send 100,000 rows of real-time data per second.  This allows any service that needs real-time analytics to use big data and solve problems in a short period.  One example of its possible usage is a utility company uses the system to analyze energy usage data from its customers to find potential outages within minutes. Using BigQuery, the utility can run a query that looks at data from electrical meters within a few miles around a certain location that didn’t show electrical use in the last five minutes.  Google has taken the necessary steps to enhance its product and change the big data industry, it doesn’t hurt that its product is priced about 75% less than its providers!

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