(SCTP) Data Analyst
About This Course
Retail (SF): Data Science Fundamentals L1
As we continue to adopt the use of technology in our everyday life, large sets of data are also being generated exponentially for our use, especially in the workplace. The demand for skills in data analytic helps businesses identify market trends and opportunities; helping to increase business performance. Data Analytics Foundational introduces essential topics including Key Concepts and Statistical Analysis, Data Set Preparation, Data Set Summarization and Data Visualization.
Retail: Introduction to Data Visualization using Microsoft Power BI
This course covers linking and modelling data in Power BI and creating visual reports that reveal data insights. The coverage includes the powerful collection of software, apps, and services that will help analyse an organisation’s data and uncover insights and trends. Power BI desktop client will be the primary focus but an introduction to the Power BI web app will also be provided.
Retail (SF): Problem Identification L4
This course covers the Identification of root causes and underlying factors of problems or situations and deduce relevant linkages and patterns to identify key impact on systems and processes.
Retail (SF): Customer Behaviour Analysis L2
This course is developed to enable learners to collect data on customer behaviours and characteristics based on established research
frameworks and historical data.
What You'll Learn
Data is essential in helping businesses understand their consumer base. Having access to real-time analytics on the performance of the business is important, especially in current times where consumer demands are constantly changing and competitions in the market are ever increasing. Hence, there is a need for Data Analysts in the Retail industry so that comprehensive analytics can be used to optimise business operations and revenue.
This programme is designed using the Technical Skills Competencies (TSCs) in Retail Framework. It covers skills courses. There are total of 5 modules in this programme.
Retail (SF): Data Science Fundamentals L1
Retail (SF): Data Analytics L2
Retail: Introduction to Data Visualization using Microsoft Power BI
Retail (SF): Problem Identification L4
Retail (SF): Customer Behaviour Analysis L2
Entry Requirements
Academic Level Required:
Minimum NITEC
Language Proficiency:
Be able to speak, listen, read, and write English at a proficiency level equivalent to the Employability Skills Workforce Skills Qualification (ES WSQ) Workplace Literacy (WPL) Level 5
Minimum Age Required:
21