Introduction to Data Analytics for Accounting Professionals from Coursera

This course covers the foundations of data analytics and how to conduct and apply this to projects in your organization. This includes the following:

- What does it mean to have a data-driven mindset? Having the right mindset will allow you to understand the problem that needs to be solved and make or recommend appropriate data-driven decisions in the context of the organization’s strategy and technologies.

- What are the key considerations when identifying, establishing, and implementing a data analytics project? This course introduces and discusses important concepts and considerations, so you are ready to be effective no matter how your organization or industry changes. This includes everything from framing the problem and defining the scope, to understanding organizational requirements and gaps, to effectively working with key stakeholders.

- What is the required technical knowledge you need so that you can understand data? Whether the data you’re looking at is financial or non-financial data, structured or unstructured, you need to understand the language of data analytics so that you can communicate effectively with colleagues and add value when using data analytics in your organization.

By completing this course, you will be in a better position to ask the right questions, add greater value, and improve the quality of services to your stakeholders.

What's inside

Syllabus

Week 1

Week 2

Week 3

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches principles of data analytics and how to apply these to projects in your organization

Introduces important concepts and considerations to help you be effective no matter how your organization or industry changes

Covers the language of data analytics so that you can communicate effectively with colleagues

Instructors are AICPA, an organization recognized for their expertise in accounting and finance

May require access to additional software or resources not readily available in a typical household or library

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Data Analytics for Accounting Professionals with these activities:

Explore Online Data Analytics Tutorials

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Exploring online tutorials can introduce you to new techniques and tools for data analytics.

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Search for online tutorials on data analytics platforms and websites.
Choose a tutorial that aligns with your interests and goals.
Follow the tutorial and complete the exercises.

Review the basics of data analytics

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Refresh your memory on the basic principles of data analytics before venturing further into the course.

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Review statistical concepts such as mean, median, and standard deviation.
Explore different types of data including structured, unstructured, and semi-structured.
Understand the data analytics process including data collection, cleaning, analysis, and visualization.

Review Statistical Methodolgy

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Taking time to review statistical methodology will help you feel more confident in your data analysis process.

Browse courses on Statistical Methods

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Review the basics of hypothesis testing.
Practice conducting a statistical analysis using a statistical software package.
Review correlation and regression techniques.

Seven other activities

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Show all ten activities

Participate in a Data Analytics Discussion Group

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Participating in discussions can help you gain different perspectives and deepen your understanding.

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Find a discussion group or forum focused on data analytics.
Introduce yourself and share your interests.
Participate in discussions, ask questions, and share your insights.

Practice Data Cleaning and Manipulation

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Practice data cleaning and manipulation will help you develop proficiency in handling and preparing data.

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Find a dataset that needs cleaning and manipulation.
Use data cleaning and manipulation tools to remove duplicate data, handle missing values, and transform data.
Verify the results of your data cleaning and manipulation.

Explore Data Visualization Techniques

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Exploring data visualization techniques will enhance your ability to communicate insights effectively.

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Find online tutorials or courses on data visualization.
Learn about different types of data visualizations, such as charts, graphs, and maps.
Practice creating visualizations using a data visualization tool.

Complete a tutorial on data visualization best practices

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Improve your data visualization skills by following a guided tutorial.

Browse courses on Data Visualization

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Choose a tutorial that covers the basics of data visualization best practices.
Follow the tutorial step-by-step and complete all the exercises.
Apply the best practices you learned to your own data visualization projects.

Develop a Data Analytics Project Proposal

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Developing a project proposal will help you understand the steps involved in a data analytics project.

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Identify a business problem that can be solved using data analytics.
Research and gather data relevant to the problem.
Develop a plan for analyzing the data.
Write a project proposal outlining your plan.

Create a Data Analytics Resource Collection

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Creating a resource collection will allow you to organize and easily access useful resources for future reference.

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Gather articles, tutorials, books, and websites related to data analytics.
Organize the resources by topic or category.
Share your resource collection with others.

Solve data analysis problems on LeetCode or HackerRank

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Sharpen your analytical skills by solving challenging data analysis problems.

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Choose a data analysis problem to solve.
Analyze the problem and identify the key variables.
Develop a solution to the problem.
Implement your solution and test it against the provided test cases.

Career center

Learners who complete Introduction to Data Analytics for Accounting Professionals will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts seek out opportunities to utilize data and technology to improve decision making within organizations. They understand not just how to collect and analyze data, but also how to communicate insights to non-technical stakeholders. This course may be particularly useful to Data Analysts because it covers key topics such as understanding the language of data analytics, identifying and framing data analytics projects, and working with key stakeholders to add value within the organization.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists are responsible for collecting, analyzing, and interpreting data in order to solve complex problems. This course may be particularly useful for aspiring Data Scientists who are looking to develop their foundational knowledge in the field. Data Scientists with a strong foundation in data analytics will be better equipped to collect, prepare, and analyze data, as well as to apply machine learning and predictive analytics to real-world problems.

See salaries and explore the career path for Data Scientist

Statistician

Statisticians use mathematical and statistical methods to collect, analyze, interpret, and present data. This course may be particularly useful for aspiring Statisticians who are looking to develop their foundational knowledge in data analytics. Statisticians with a strong foundation in data analytics will be better equipped to design and conduct statistical studies, as well as to develop and apply statistical models.

See salaries and explore the career path for Statistician

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems and improve the efficiency of systems. This course may be particularly useful for aspiring Operations Research Analysts who are looking to develop their foundational knowledge in data analytics. Operations Research Analysts with a strong foundation in data analytics will be better equipped to collect, analyze, and interpret data, as well as to develop and apply mathematical models to real-world problems.

See salaries and explore the career path for Operations Research Analyst

Business Intelligence Analyst

Business Intelligence Analysts use data to identify trends and patterns, as well as to develop and implement solutions to business problems. This course may be particularly useful for aspiring Business Intelligence Analysts who are looking to develop their foundational knowledge in data analytics. Business Intelligence Analysts with a strong foundation in data analytics will be better equipped to collect, prepare, and analyze data, as well as to develop and implement data-driven solutions.

See salaries and explore the career path for Business Intelligence Analyst

Financial Analyst

Financial Analysts are responsible for gathering and interpreting financial data in order to make recommendations for investments or financial decisions. This course can help aspiring Financial Analysts to gain a better understanding of the key concepts of data analytics, as well as how to apply these concepts to real-world financial data. Furthermore, this course can help Financial Analysts develop their communication skills, which are essential for presenting their findings to clients.

See salaries and explore the career path for Financial Analyst

Data Engineer

Data Engineers are responsible for designing, building, and maintaining data pipelines that collect, transform, and store data. This course may be particularly useful for aspiring Data Engineers who are looking to develop their foundational knowledge in data analytics. Data Engineers with a strong foundation in data analytics will be better equipped to design and implement data pipelines that are efficient, scalable, and reliable.

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Machine Learning Engineer

Machine Learning Engineers are responsible for designing, building, and deploying machine learning models. They use data to train and evaluate models that can make predictions about future events. This course may be particularly useful for aspiring Machine Learning Engineers who are looking to develop their foundational knowledge in data analytics. Machine Learning Engineers with a strong foundation in data analytics will be better equipped to collect, prepare, and analyze data, as well as to develop and deploy machine learning models that are accurate and reliable.

See salaries and explore the career path for Machine Learning Engineer

Management Consultant

Management Consultants advise businesses on how to improve their performance. Many Management Consultants find that they need to do their own research and analysis in order to give well-informed advice. This course can help Management Consultants build a foundation in data analytics, including how to identify data sources, clean data, and analyze results. Additionally, this course may be helpful for Management Consultants when working with clients in fields such as accounting and finance.

See salaries and explore the career path for Management Consultant

Quantitative Analyst

Quantitative Analysts use mathematical and statistical methods to analyze financial data and make investment decisions. This course may be particularly useful for aspiring Quantitative Analysts who are looking to develop their foundational knowledge in data analytics. Quantitative Analysts with a strong foundation in data analytics will be better equipped to collect, prepare, and analyze financial data, as well as to develop and apply financial models.

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Risk Analyst

Risk Analysts use data to identify and assess risks to organizations. This course may be particularly useful for aspiring Risk Analysts who are looking to develop their foundational knowledge in data analytics. Risk Analysts with a strong foundation in data analytics will be better equipped to collect, prepare, and analyze data, as well as to develop and implement risk management strategies.

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Fraud Investigator

Fraud Investigators use data to investigate and prevent fraud. This course may be particularly useful for aspiring Fraud Investigators who are looking to develop their foundational knowledge in data analytics. Fraud Investigators with a strong foundation in data analytics will be better equipped to collect, prepare, and analyze data, as well as to identify and investigate fraudulent activities.

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Data Governance Analyst

Data Governance Analysts are responsible for developing and implementing policies and procedures to ensure the quality, integrity, and security of data. This course may be particularly useful for aspiring Data Governance Analysts who are looking to develop their foundational knowledge in data analytics. Data Governance Analysts with a strong foundation in data analytics will be better equipped to understand the importance of data quality and integrity, as well as to develop and implement data governance policies and procedures.

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Auditor

Auditors may use data analytics to improve the efficiency and effectiveness of the audit process. This course may be particularly helpful for Auditors who are looking to expand their skillset and gain a competitive edge in the job market. By understanding the foundations of data analytics, Auditors can use their skills to identify risks, detect fraud, and improve the overall quality of their audits.

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Accountant

Accountants are responsible for preparing, analyzing, and interpreting financial statements. Though this course does not offer specific training in accounting principles, it may be helpful for Accountants who are looking to develop their data analytics skills to gain a competitive edge in the job market. Accountants with data analytics skills can use their abilities to improve the accuracy and efficiency of their work, as well as to identify trends and patterns that may be missed by traditional accounting methods.

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