Data Analytics and Business Intelligence

Course content

11 modules

Data types, structures and common business data sources

KPIs, metrics and dimensions: building an analytics brief

Descriptive statistics: mean, median, variance and distributions

Probability basics for analysts: sampling, confidence and risk

Correlation versus causation and common analytical pitfalls

Hypothesis testing intuition: A/B tests and p-values in plain language

Data ethics, privacy and responsible use

Excel from zero: workbooks, cells, data entry and formatting

Excel essentials for analytics: formulas, tables and named ranges

Introduction to Power Query in Excel: import, clean and transform

Building your first KPI dashboard in Excel

About this course

Build practical skills to analyse data, solve business problems and communicate defensible insights. This course takes you from foundational data and statistical thinking through Excel, SQL, Python, data visualisation, Power BI, advanced analytics, data engineering fundamentals, automation, storytelling and stakeholder management. You will complete practical projects throughout the course and build portfolio evidence including an insight brief, SQL notebook, automated analytics report, Power BI dashboard, decision memo, automated pipeline and a final capstone project. The course is designed to help you develop the technical, analytical and communication skills required to work with real-world data and make informed business decisions.

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