Data Analytics
Develop the knowledge and practical skills needed to collect, organise, analyse and communicate data for informed decision-making.
About This Course
Build a strong foundation in data analytics and learn how information can be transformed into useful insights.
This course introduces students to the fundamentals of data analytics and explains how data is collected, organised, explored and interpreted to support informed decisions. Students will develop practical knowledge of working with datasets, descriptive analysis, data visualisation, analytical tools and responsible data-driven decision-making.
Course Information
Key information about the SCS-0004 programme.
What You Will Learn
Throughout the programme, students will develop practical knowledge across the core areas of data analytics.
Data Analytics Fundamentals
Understand how data is collected, organised, explored and interpreted to support informed decisions.
Working with Data
Organise, clean, sort and prepare datasets for meaningful analysis.
Descriptive Analysis
Use descriptive statistics and analytical techniques to understand and summarise datasets.
Data Visualisation
Present information clearly using appropriate charts, graphs and other visualisation methods.
Data Analysis Tools
Develop practical skills using spreadsheets, formulas, filtering, sorting and pivot tables.
Data-Driven Decision-Making
Interpret analytical findings and understand how data can support responsible decision-making.
Course Modules
The SCS-0004 programme consists of six core modules.
Introduction to Data Analytics
This module introduces the fundamentals of data analytics and explains how data is collected, organised, explored and interpreted to support informed decisions. Students will learn about different types of data, basic data analysis processes, data quality, data sources and the role of analytics in organisations and everyday situations.
Working with Data
This module develops practical knowledge of working with datasets and introduces common techniques for organising, cleaning, sorting and analysing data. Students will learn how to work with rows, columns, variables and records, identify data quality issues, and prepare datasets for further analysis using appropriate tools and methods.
Descriptive Data Analysis
This module introduces descriptive analysis techniques used to summarise and understand datasets. Students will explore measures of central tendency, measures of variation, distributions, frequency tables and comparisons. The module also explains how descriptive statistics can provide a clear overview of data before more advanced analysis is performed.
Data Visualisation and Communication
This module introduces data visualisation and explains how charts, graphs and other visual methods can be used to communicate information effectively. Students will learn how to select appropriate visualisations, organise information clearly, interpret charts and present analytical findings to different audiences. The module also covers visual accuracy, readability and responsible communication of data.
Data Analysis Tools and Techniques
This module introduces common tools and techniques used to perform practical data analysis. Students will explore spreadsheets, formulas, data sorting and filtering, pivot tables, basic analytical functions and methods for presenting and reviewing analytical results. The module develops practical skills for working with datasets and preparing useful information for decision-making.
Advanced Data Analysis and Decision-Making
This module introduces more advanced concepts used to interpret data and support informed decision-making. Students will explore relationships between variables, basic predictive thinking, data-driven decision-making, analytical limitations and the responsible use of data. The module brings together the skills developed throughout the course and prepares students to apply data analytics to practical situations.
Learning Outcomes
On successful completion of the course, students should be able to apply data analytics knowledge to practical situations.
Understand Data Analytics
Explain the fundamental concepts, processes and role of data analytics.
Work with Datasets
Organise, clean and prepare datasets for analysis.
Analyse Data
Apply descriptive techniques to summarise and interpret information.
Visualise Information
Select and create appropriate visualisations to communicate analytical findings.
Use Analytical Tools
Apply practical data analysis tools and techniques to real-world datasets.
Support Decisions
Interpret analytical results and use data responsibly to support informed decisions.
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