MIS 2502: Data Analytics
Big Data
Big Data is a term that is commonly correlated with massive data that is created through a variety of sources that can range from the environment, mobile devices, electronic medical records, and imaging and laboratory studies. Big Data includes three very important parts, they are velocity, volume, and variety (Pence). Velocity is the speed of data flowing in as well as the data being analyzed. Volume is the sheer size of data that is being stored and variety is the diversity of data. Though sometimes, big data is filled with both positive and negative potential, Big Data will allow companies to better understand their customers. In our society, big data has been a big facilitator for innovation, reconstruction, and advancement (Barton). It continues to receive attention from researchers and professionals in all different kinds of areas, such as academia, the government, and even research.
The goal of MIS 2502 is to help students analyze data and learn how to present insights from business data as well as create data models and data warehouses based on business rules. In class, we used R to help with data mining, which uses the discovered information from Big Data to assist with making business decisions. We also used ETL, which is the extract, transform, and loading process, to help format data to ensure that all data is formatted the same way so that when information is needed from a specific data set businesses are finding all the correct information. The importance of big data is that it can help with more accurate identification of customer characteristics, for example Amazon and Netflix use Big Data to help suggest products that customers might be interested in based on similar purchases form other customers.
References:
Barton, Amy J. “Big Data.” Journal of Nursing Education 55.3 (2016): 123-4. ProQuest. Web.
30 Apr. 2017.
Pence, Harry E. “What Is Big Data and Why Is It Important?” Journals.sagepub.com.libproxy.temple.edu. Baywood Publishing Co., Inc., 23 Dec. 2014. Web. 30 Apr. 2017.