This module explores the structure and components of the modern data ecosystem. You will examine different data structures, sources, and file formats, along with repositories such as databases, data warehouses, and data lakes. The module also introduces ETL processes, programming languages used by data professionals, and the foundations of big data and its processing tools.

This module focuses on the processes used to identify, collect, and prepare data for analysis. You will learn how data is gathered and imported from different sources and how data wrangling techniques help transform raw data into analysis-ready datasets. The module also introduces common tools, techniques, and best practices used for data cleaning and preparation.

This module explores how statistical analysis and data mining techniques are used to uncover patterns, trends, and relationships in data. You will examine tools and methods used to analyze data and generate meaningful insights. The module also introduces data visualization and storytelling techniques used to communicate analytical findings effectively.

This module explores career pathways and skill development opportunities for aspiring data analysts. You will apply key data analysis processes—including gathering, wrangling, analyzing, and visualizing data—through a practical case study. The module concludes with a final project that allows you to demonstrate your understanding of the end-to-end data analysis workflow.