Introduction

With rapid advances in technology bringing change to the workplace, business and finance leaders need to be sure that decisions they make are rooted in a deep understanding of data available to them. As guardians of organisational data it is essential that finance teams are at the forefront of these conversations, and that they have the necessary skills, and level of data literacy, to provide the forward-looking insights required to support their organisations with strategic decision-making.

ACCA has created the Certificate in Data Analytics for Finance Professionals to support business professionals who wish to upskill themselves in this vital area. By using industry specific best practice and real world examples, this online, on-demand course explores the principles of data analytics, highlights both essential and advanced skills, and demonstrates how to apply them in order to provide data-driven insights, to support controlled, strategic change within their organisations.

Learners will learn about big data, the various sources of data, types of analytics, and become familiar with the range of freely available tools and techniques required to extract, manipulate, interpret and present data. They’ll also learn about the need to be both sceptical and ethical when working in the data analytics field.

Developed in response to insights from over 900 finance leaders, the Certificate in Data Analytics for Finance Professionals can be used as verifiable CPD and to demonstrate your skillset to current or future employers.

Learning outcomes

By completing this course, you will be able to:

• identify and describe the four primary types of data analytics
• apply key data analytics techniques within the context of accounting and finance ​
• recognise the role of AI, Machine Learning and data manipulation tools (Python, R, SQL) in the ethical manipulation and analysis of datasets​
• use modern data tools, including both Tableau and PowerBI, to analyse datasets to identify patterns and trends
• visualise and communicate data insights effectively, to empower decision-making
• identify key data governance and security practices related to data analytics and plan for their effective implementation.

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