Self-Paced • 30 Hours • Digital Badge
Build practical data analytics skills with Excel, SQL and Tableau.
Data Analytics Essentials is a beginner-friendly course that helps learners gather, transform, query and visualize data, then turn those results into portfolio-ready work.
- Beginner-Friendly
- Portfolio-Oriented
- Career-Focused
- No Formal Prerequisites
Course Overview
Learn the fundamental tools of a data analyst
This course introduces the essential workflow of data analytics: investigating data with spreadsheets such as Excel, querying relational databases with SQL, and presenting insights through dashboards and visualizations in Tableau.
By the end of the course, learners begin building an analytics portfolio that demonstrates practical skills in Excel, SQL and Tableau.
Who This Course Is For
Designed for learners who want a practical entry point
A strong fit for high school learners, vocational students, college and university students, IT and non-IT learners, and career changers who want job-relevant analytics foundations.
Excel for data work
Use Excel to gather, inspect, sort, filter, format and calculate data, then build charts and fix issues using functions such as VLOOKUP or XLOOKUP.
SQL for structured queries
Learn how relational databases work, write SQL queries, and combine data from multiple tables using joins and related query functions.
Tableau for visualization
Create visualizations, understand dashboards and present findings more clearly through modern data storytelling tools.
What You Will Learn
- Explain how data analytics projects are organized.
- Perform initial data gathering and investigation using a spreadsheet.
- Use Excel functions and formulas to transform data for analysis.
- Obtain and prepare appropriate data for analysis.
- Perform statistical analysis on data.
- Formulate SQL queries to extract and combine data from multiple tables.
- Create visualizations and dashboards using Tableau.
- Understand ethics and bias in data analytics.
- Revisit your portfolio and continue building your skillset.
Requirements & Recognition
- No formal prerequisites.
- Introduction to Data Science is recommended for beginners.
- Course delivery: self-paced.
- Recognition: digital badge.
- Physical equipment: not required.
- Recommended next course: Python Essentials 1.
Module Structure
10 modules from raw data to portfolio growth
Why It Matters
Practical analytics skills that translate into real work
Analytics is valuable across industries. This course helps learners understand how to work with data, how to communicate results clearly, and how to build a visible starting point for future projects and career growth.
Start Learning
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