CLMG (6 credits - II sem. - OP | SECS-P/07) -
M (6 credits - II sem. - OP | SECS-P/07) -
IM (6 credits - II sem. - OP | SECS-P/07) -
MM (6 credits - II sem. - OP | SECS-P/07) -
AFC (6 credits - II sem. - OP | SECS-P/07) -
CLELI (6 credits - II sem. - OP | SECS-P/07) -
ACME (6 credits - II sem. - OP | SECS-P/07) -
DES-ESS (6 credits - II sem. - OP | SECS-P/07) -
EMIT (6 credits - II sem. - OP | SECS-P/07) -
GIO (6 credits - II sem. - OP | SECS-P/07) -
DSBA (6 credits - II sem. - OP | SECS-P/07) -
PPA (6 credits - II sem. - OP | SECS-P/07) -
FIN (6 credits - II sem. - OP | SECS-P/07) -
AI (6 credits - II sem. - OP | SECS-P/07)
Suggested background knowledge
For a fruitful and effective learning experience, it is recommended some preliminary experience in statistical analysis (such as summary statistics (visual and graphical), regression analysis, ANOVA, etc) as well as applying these analyses via Microsoft Excel. In addition, it is also recommended to have basic knowledge in accounting such as financial statements, auditing report, tax, etc.
Mission & Content Summary
MISSION
Managers need to make investment decisions, manage risks, and ensure compliance with regulatory policies and requirements. In a rapidly changing and competitive global market, accountants play a pivotal role in supporting managerial decision-making. This course introduces the tools and approaches of fulfilling the supportive functions of accountants from a data analytics perspective and a combination of financial and managerial accounting. Specifically, the course facilitates the appreciation of big data view on the complexity of the firm and the understanding of the relationships between the operations and financial statements. The course synthesizes theory and application to prepare students with the approaches of diagnosing problems and issues, analyzing relevant information, making responsible and ethical decisions, and reporting decision results and recommendations, incorporating both the qualitative and quantitative data from the firm, the intermediaries, and the capital market. The course focuses on analytical techniques and provides hands-on experience to develop business analytics skills.
CONTENT SUMMARY
The main topics of the course are as follows:
- Introduction to the modern accounting environment and data analytics for accounting
- Understanding and mastering the Data
- Developing and implementing analysis plan and analyzing the findings
- Communicating results and recommendations
- Audit Data Analytics
- Managerial Analytics
- Financial Statement Analytics
- Tax Analytics
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Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
- Recognize when and how data analytics can address business questions
- Comprehend the process needed to clean and prepare the data before analysis
- Identify and evaluate the veracity of sources of unstructured and structured data for use in analysis.
- Recognize what is meant by data quality, be it completeness, reliability, or validity
- translate a decision problem into a corresponding quantitative model
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APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
- Apply critical analytical thinking to identify and frame business problems for analysis
- Perform basic analysis to understand the quality of the underlying data and their ability to address the business question
- Demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that allows enhanced analysis
- Identify and implement an approach that will use statistical data analysis to draw conclusions and make recommendations on a timely basis
- Solve accounting and business related problems using appropriate analytics tools
- Create visualizations of data to provide clear insights into accounting and other business data, to effectively communicate those insights, and to support recommendations
- Recommend appropriate actions to address real-world problems in accounting practice
- Discuss ethical issues as they pertain to the performance and use of data analysis
- Write effectively to communicate analysis results in the framework of the business problem
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