Introduction to Career Skills in Data Analytics

Whether you're exploring a career change or building new skills, understanding data analytics can open doors across industries. In this course, instructor Robin Hunt provides a clear, practical roadmap for anyone looking to break into data analytics—no technical background required. Robin steps through the essentials, from defining data analysis and business intelligence to identifying, preparing, transforming, modeling, and visualizing data using tools like Excel, SQL, and Power BI.

Robin introduces key concepts such as data quality, data governance, and the difference between data-driven and data-informed decision-making. Along the way, she also helps you explore AI fluency with Copilot and learn questioning techniques to collect and interpret the right data. By the end, you have the foundation to map out your own path in data—whether that leads to data analysis, data engineering, visualization, or beyond.

Learning objectives
Define data analysis and common data roles, and develop a foundation in data fluency.
Explain business intelligence and its value to organizational decision-making.
Apply questioning techniques to identify, collect, and interpret data from various sources and structures.
Assess and prepare data for transformation using key Excel techniques such as removing duplicates, splitting text, and validating data.
Transform data using Excel formulas and pivot tables, and write basic SQL queries using select statements and joins.
Create reports and apply visualization best practices in Power BI.
Describe relational databases and model data for use in Power BI.
Use Copilot to support and enhance your data analysis workflow.