Big Data
What is Big Data?
Source: Forbes.com
While big data is a popular buzzword that means different things to different people, the term can be best defined using the three V’s: volume, variety and velocity. The first V, volume, is what most people consider when they think of big data. Businesses have more data available to them now than ever before. What people may not realize is the large variety of data available to businesses. Big data varies from traditional structured data in rows and columns to unstructured data in text, audio, and video form. Companies are using social listening programs to gain insight from unstructured social media data on Twitter and Facebook. As businesses have begun collecting new forms of data, the velocity at which the data is created and analyzed has increased drastically. There is a need for certain types of data to be analyzed in real time to maximize business value. The decreased cost of computer storage has made big data more beneficial to businesses in recent years.
Big D
ata in MIS
Having lots of data is not a business solution by itself. IT professionals must know how to store, transform, and analyze data to create actionable insights for their business. I have been exposed to these principles in the MIS 2502 Data Analytics course. This course taught me how to store data using MySQL, transform data using Microsoft Excel, and analyze data using SAS Enterprise Miner. The data I worked with in MIS 2502 was primarily structured data. In the future I would like to learn how to analyze unstructured data since the digitalization of practically everything is creating vast amounts of unstructured data.
Big Data in Action
The Coca-Cola Company utilizes one of the most innovative big data practices to date. Manufacturing a consistent tasting fruit juice can be difficult when the optimal growing season is only three months long. In order to produce Minute Maid orange juice with a year-round consistent taste, Coca-Cola uses its Black Book algorithm to create an ideal blend. Black Book analyzes up to 1 quintillion decision variables from both structured and unstructured data. The different variables analyzed by Black Book include satellite imagery, weather data, expected crop yields, acidity and sweetness rates, and regional consumer preferences. Coca-Cola’s Black Book model is a terrific example of how a variety of data can be used to create actionable insights.