This interdisciplinary data analytics course provides a comprehensive understanding of the data analytics process within the realm of accounting and finance. With the increasing volume of structured and unstructured data, there is a growing need for a data-driven approach to decision-making in these fields. Accountants and finance professionals must adopt a data analyst mindset to stay ahead in the era of Big Data.

Throughout the course, learners will explore various accounting and finance concepts through the application of data analytics. They will not only develop the skills to ask relevant questions but also learn how to effectively work with data using tools such as Excel and Tableau. By the end of the course, learners will be able to interpret the results of their analyses and make informed decisions.

The course employs a simple framework, known as QDAR, to foster an analytical mindset among learners. This framework comprises four key components:

1. Ask the right Questions: Learners will learn how to identify and formulate appropriate questions to address accounting and finance issues.
2. Understand and retrieve the relevant Data: Learners will gain knowledge of different data types and learn techniques for data retrieval and cleaning.
3. Conduct various data Analyses: Learners will acquire the skills to perform different data analyses to obtain insights and answers to their questions.
4. Communicate the Results: Learners will be trained on effectively presenting their findings to decision-makers through the use of graphs, visualizations, and reports.

By following this framework, learners will develop a strong foundation in data analytics and enhance their ability to approach accounting and finance challenges using a data-driven approach.