Certificate in Data Analytics (CertDA)
- Offered byACCA
Certificate in Data Analytics (CertDA) at ACCA Overview
Duration | 4 hours |
Mode of learning | Online |
Credential | Certificate |
Certificate in Data Analytics (CertDA) at ACCA Highlights
- Earn a certificate of completion
Certificate in Data Analytics (CertDA) at ACCA Course details
- for those with a basic knowledge of numeracy and possibly statistics, particularly those employed in, or aspiring to work in, a wide range of accounting and finance related roles
- The learners will learn:
- how to use commercial awareness to articulate business questions
- identify and manipulate relevant data and deeply analyse it by applying appropriate techniques.
- how findings from analysis can and should be visualised and communicated, enabling relevant stakeholders to make sound business decisions
- learn and understand ethical security issues around data analytics.
- The ACCA Certificate in Data Analytics (CertDA) is aimed at business professionals who wish to develop their understanding of data, and the skills and techniques available for data analytics
- Using real practical business examples, learners are able to develop an understanding of how data analytics and data modelling can be used to garner business insights
- Learners will learn about big data, the various sources of data, types of analytics, and become familiar with the range of 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
Certificate in Data Analytics (CertDA) at ACCA Curriculum
The CRISP framework for data analytics
Business understanding
Data understanding
Data preparation
Data modelling
Data evaluation
Deployment
Big data and data analytics
What is big data?
The 3 Vs of big data
The value and lessons to be learned from big data
Sources of data
Interal
External
Types of analytics
Descriptive analytics
Predictive analytics
Prescriptive analytics
Data analytics methodologies
Robotics
Artificial intelligence
Machine learning
Mainstream tools and key applications of data analytics
Tool and applications for descriptive analytics
Tools and applications for predictive analytics
Tools and applications for prescriptive analytics
Data visualisation and communication
What is data visualisation?
The purpose of data visualisation
The benefits of data visualisation
The history of data visualisation
Types of visualisation - comparison
Types of visualisation - composition
Types of visualisation - relationship
What makes good visualisation?
Scepticism in data analytics
Ethical considerations in the use of data
End of units data analysis activity
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