Reference no: EM133092112
Purpose
Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to delineate business trends, determine the quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions.
Big data analytics is a topic fraught with both positive and negative potential. Big data is defined not just by the amount of information involved but also by its variety and complexity, as well as the speed with which it must be analyzed or delivered. The amount of data being produced is already incredibly great, and current developments suggest that this rate will only increase in the near future. Improved service should result as companies better understand their customers, but it is also possible that this data will create privacy problems. Thus, big data is important not only to students who hope to gain employment using these techniques and those who plan to use it for legitimate research, but also for everyone who will be living and working in the 21st century.
Assignment Instructions
First, navigate to the Academic Tools area of this course and select Library then Required Readings to review the Unit 8 videos covering facets associated with big data. It is very important that you watch the Unit 8 videos before completing the assignment.
Perform research on big data use cases via the Internet and Purdue University Global Library. Use the article at the following website as a starting point for your research:
Big Data Use Cases
Select one use case from the list below to be the topic of your paper.
360° View of the Customer
Fraud Prevention
Security Intelligence
Data Warehouse Offload
Price Optimization
Operational Efficiency
Recommendation Engines
Social Media Analysis and Response
Preventive Maintenance and Support
Internet-of-Things (IoT)