BIG DATA ANALYTICS IN ACCOUNTING & FINANCE (2 SCU)

Learning Outcomes:

On successful completion of this course, students will be able to: Explain a collection of computer technologies that support big data analytics; Classify big data analytics activities; Analyze problems in big analytics.

Topics:

1. What Are Big Data and Analytics? An Overview of Big data Intelligence, Analytics, and Data Science;
2. What Are the Strategy and Business Applications of Big Data?;
3. Big Data History, Big Data Sources and Characteristics;
4. Big Data Platforms and Operating Tools Accounting Activities. Big Data Concepts and Tools;
5. Big Data End User and Accounting Tools;
6. Examples of big data;
7. Big Data in the Accounting Department;
8. Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization;
9. Descriptive Analytics II: Big data Intelligence And Data Warehouse;
10. Predictive Analytics I: Data Mining Process, Methods, And Algorithms;
11. Predictive analytics II: Text, Web, and Social Media Analytics;
12. Ethics and privacy with big data;
13. Future trends, privacy and managerial considerations in analytics.