Darawan Phommasith
Intro to MIS
Professor Smoolca
Big data
Big data is the term used to describe the exponential growth and availability of data, both
structured and unstructured. Big data may be just as important to a business and society as
the Internet has become. Why? This is because more data may lead to more accurate
analyses!
Technology Projects:
1. What is the technology and why is it important?
With the existence of Big data more accurate analyses can be done as well as confident
decision making. And with better judgment for decision making it can lead to greater
operational efficiencies, cost reductions and reduced risk for a business and even a career.
2. Where and when did it originate and how did it develop?
Big data started in the 21st century with likes from companies such as Google, eBay, and
Facebook, and LinkedIn. In fact those websites started from Big data.
In a 2001 research report and related lectures, META group (now Gartner) analyst Doug
Laney defined data growth challenges and opportunities as being three dimensional and
increasing volume in terms of amount of data and the Velocity (speed) of the data was
flowing inward and outward as well as Variety ranging from data types and sources.
Gartner and now most of the industry continues to use “3Vs” model for describing big
data. This updated the definition of big data as follows:
“Big data is high volume, high velocity, and/or high variety information assets that
require new forms of processing to enable enhanced decision making, insight
discovery and process optimization.”
The “3V’s”
a. Volume – there is a large amount of information amounting to Terabytes or Petabytes of
data
b. Velocity – data is not only coming in quickly but should be processed quickly too!
c. Variety – data is coming in, in several formats and several different sources
4. Who are the key vendors/products in this market and what are their pros and
cons?
UPS is no stranger to big data, having begun to capture and track a variety of package
movements and transactions as early as the 1980s.The company now tracks data on 16.3
million packages per day for 8.8 million customers, with an average of 39.5 million
tracking requests from customers per day. The company stores more than 16 petabytes of
data.
Much of its recently acquired big data, however, comes from telematics sensors in more
