Huge data!
Everything we do online (and in some cases offline) somewhere is recorded and made into a database that is known as Big Data. Big data can be utilized for any number of uses,
“Everyday, we create 2.5 quintillion bytes of data–so much that 90% of the data in the world today has been created in the last two years alone.” This interesting insight is provided on the IBM.com website. For those of you who don’t know, IBM are a massive international technology and consultation company, one of the many companies interested in utilizing big data. IBM being the huge company they are would be foolish to not investigate the use of this new method.
Big data can covers 3 dimensions having expanse variety of data categories, including structured and non-structured data (eg audio, text, streams etc), it has velocity of streaming at high speed even though it’s crunching huge numbers of data. Lastly there is a large volume of data, an extremely large volume of data, hence the name big data. These three dimensions that big data span over give it the edge of any other type of data analysis. SAS considers another two extra dimensions, complexity and variability. Complexity refers to the multiple sources and platforms that the data can originate from and be developed on. Variability refers to trends in social media that big data crosses. This is where the velocity and variety intersect at certain periodic points.
There are several advantages to businesses that utilize big data, they can use it to better understand their customers and in turn market their products or services better to reach them and grow their business. As well as determine the cause of failures and consequently address such failures.
SAS are an analytics software company, one of the world’s largest private software companies in the world. They posted this video almost a year ago
A company that used SAS’s big data analysis techniques is UPS (United parcel service) they have already capitalized on these strategies and are reaping the rewards. UPS tracks 16.3 million packages a day for 8.8 million customers, averaging 39.5 million requests for tracking every day. This incredibly large number translates to 16 petabytes of data. This diagram shows the size of one petabyte. These 16 petabytes would be impossible to sort through until the alleviation use of big data.
(source: http://hwzone.co.il/hwzone.co.il/originals/news_images/PB-disc5.jpg)
Using tracking telematics sensors in over 46,000 vehicles, data is gained from the vehicles. Including speed, direction, braking, navigation and driver trainer performance. In 2011 the company saved over 8.4 million gallons of fuel by cutting 85 million miles from every day routes. This information would not have been possible without big data.
In a world with so much data, that is exponentially increasing, we need big data analytics to better understand the vast numbers of data. Without big data analytics the data will be rendered almost useless.
References
Eric Lundquist. 2014 "Big Data Can Solve Small Problems." http://www.eweek.com/database/big-data-can-solve-small-problems.html Accessed 3rd May 2014
Author Unknown. “IBM” Accessed 3rd May 2014 http://en.wikipedia.org/wiki/IBM
Thomas H. Davenport and Jill Dyche, "Big Data in Big Companies," May 2013.
SAS. 2013. "Big Data, What is it and why it matters" www.sas.com/en_us/insights/big-data/what-is-big-data.html Accessed 3rd May 2014
IBM, "Bringing big data to the Enterprise" Accessed 3rd May 2014 www-01.ibm.com/software/au/data/bigdata/












