Community Platform
Interests
  • Data analytics
  • Database management systems
  • Design
  • Entertainment
  • more...
This Year
No Points
Total
920 Points
MIS Badge

Click here
to validate the recipient

MIS2502 Extra Credit: Big Data

Big data is the need for a new model to deal with the ability to have a stronger decision-making, insight into the ability to find and optimize the process to adapt to the massive, high growth and diversification of information assets.  There are Big data 5V features that IBM come up with: Volume (large), Velocity (high speed), Variety (diversity), Value (low-value density), Veracity (authenticity).

 

The strategic significance of big data technology is not to grasp the huge data information, but in the significance of these data for professional processing. In other words, if we compare the big data to a kind of industry, then the key to achieving profitability in this industry, is to improve the data processing capacity, through the processing of the data to achieve value-added. Therefore, big data is related to data analytics. Big data builds on Advanced Analytics section of our MIS2502 class. The big data movement, such as analysis, seeking information from the data collection, and transformed into a commercial advantage. An effective organization places information and relevant decisions in the same place. In the era of big data, information is created and transferred. People who know the problem need to put together the right data and have the skills to solve the problem, in order to effectively use them.

 

Over the years, Amazon has used these data to establish a recommendation system to recommend products to people who browse Amazon.com. In 2003 they have used project item similarity methods from collaborative filtering. They use customer click-stream data and the data of their purchase history to show each user-customized results on customized web pages.

 

References:

Monnappa, Avantika. “Data Science vs. Big Data vs. Data Analytics.”Simplilearn.com. Simplilearn, 24 Mar. 2017. Web. 28 Apr. 2017.

Media, OReilly. “Volume, Velocity, Variety: What You Need to Know About Big Data.” Forbes. Forbes Magazine, 11 Mar. 2012. Web. 28 Apr. 2017.

Lohr, Steve. “The Age of Big Data.” The New York Times. The New York Times, 11 Feb. 2012. Web. 28 Apr. 2017.

 


Skip to toolbar