Data Analytics in Accounting and Finance
About this courseSkip About this course
This data analytics course takes an interdisciplinary approach to demonstrate the data analytics process in the context of accounting and finance. The growing volume of both structured and unstructured data has pushed forward a more data-driven form of decision-making in accounting and finance. In order to keep up with the Big Data era advancements, accountants and finance professionals need to have a data analyst mindset to excel in their jobs.
This course will illustrate different concepts of accounting and finance with the application of data analytics. It will not only help the learners to develop their skills to ask the right questions but also teach them how to master the data and use different tools like Excel and Tableau to analyze the data. In the end, the learners will be able to interpret the results and make their decisions effectively.
This course will use a simple framework that helps the learners to develop an analytical mindset. This framework (QDAR) has four major components:
1. Ask the right Q uestions to address an issue in accounting or finance contexts.
2. Understand the different data types and how to retrieve and clean D ata.
3. Conduct different data A nalyses to answer the questions
4. Communicate the R esults to the decision-makers using graphs, visualizations and reports.
The whole course will cover different aspects of the framework in conjunction with different types of analyses. There will be additional datasets for the verified learners through which they can practice what they have learned during the course.
At a glance
- Institution: HKPolyUx
- Subject: Data Analysis & Statistics
- Level: Introductory
- Prerequisites: None
- Language: English
- Video Transcript: English
- Associated skills: Unstructured Data, Finance, Tableau (Business Intelligence Software), Big Data, Data Analysis, Accounting, Decision Making
What you'll learnSkip What you'll learn
- Understand how data analytics are used to drive decisions in accounting and finance contexts.
- Form hypothesis, design models, interpret results, and formulate actionable recommendations.
- Gain practical experience using Excel and Tableau to apply data science and analytics with accounting finance datasets.