Introduces data analytics, its applications and the processes used to transform raw data into useful insights.
Teaches learners how to identify, collect and evaluate data from different sources.
Introduces methods for organising, storing and managing datasets for analytical purposes.
Develops practical spreadsheet skills for organising, calculating and analysing data.
Introduces advanced spreadsheet techniques for analysing larger datasets and producing useful business insights.
Teaches learners how to identify and correct errors and inconsistencies before performing analysis.
Introduces statistical concepts used to summarise, compare and interpret data.
Develops practical SQL skills for retrieving and analysing data stored in relational databases.
Teaches learners how to combine data from multiple tables and perform more advanced database analysis.
Introduces Python as a practical programming tool for data processing and analysis.
Introduces Python libraries commonly used to manipulate, analyse and explore datasets.
Teaches learners how to explore datasets and identify trends, relationships, patterns and anomalies.
Develops skills for communicating analytical findings through clear and effective visualisations.
Teaches learners how to convert analytical results into interactive dashboards and management information.
Introduces methods for structuring data and using analytical techniques to answer business questions.
Introduces basic predictive techniques used to identify future trends and support forecasting
Develops awareness of responsible data use, privacy, security, quality and ethical decision-making.
Learners apply the complete analytics workflow to a real-world dataset and produce a professional analytical report.