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Join me on a learning journey in Power BI and PostgreSQL, to create an industry-standard, interactive and comprehensive report. We will be working on an online retail dataset (120,000 records) from an anonymised multinational retail company. We will also and extracting valuable insights to inform business decisions.

📌 The first part of the project focuses on data extraction, cleaning and modelling. We will perform ETL on the data: 1) extract data (E) from four different cloud and local sources; 2) transform (T) the data in Power Query, and 3) load the data back to Power BI. Finally, we will create our STAR-based data model, including a dates table and relevant hierarchies.

📊 The second part consists on the development of an interactive multi-page Power BI report. First, we will a table of key measures in DAX. We will then build interactive-multi-page report containing 35 visualisations, from KPIs to predictive modelling.

💻 The third objective focuses on creating custom SQL queries to generate powerful insights outside the Power BI environment. Why do we want to do this? Not all clients will have access to Power tools like Power BI desktop or Service. We want to ensure that data insights can still be extracted and shared with a broader audience.

This documentation includes a detailed guide into Power BI data modelling and reporting. Let's dive in!