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Data & Analytics Lecturer / Staff Student Public

1. Power BI Analytics

#Power BI #Analytics #Data Visualization #Weekend
Jun 15, 2026 · 15:30 → 15:30 Innovation Hub, Phnom Penh 0 / 30 enrolled
About this programme

Course outline.

Course Description
Data Analytics and Visualization with Power BI is designed for individuals seeking to enhance their skills in data analysis and reporting. Participants will learn the fundamentals of Power BI, including how to create insightful reports and interactive dashboards, perform data modeling, utilize DAX for calculations, and clean and transform data for analysis. Whether you are a beginner or looking to refine your skills, this course provides practical knowledge and hands-on experience to equip you for roles in data analytics.

What you'll get

Programme highlights.

Industry-led teaching

Live materials from practitioners working in the field today.

Hands-on exercises

You'll apply what you learn through structured workshops and case studies.

Mentor access

Personal contact with the instructor for questions and feedback.

UTE Certificate

A signed certificate of completion you can add to your CV.

Course outline

What we'll cover.

  1. 01

    Course Outlines

    Chapter 1: Introduction to Data Analytics and Power BI • Overview of Data Analytics • Introduction to Power BI and its Components • Understanding the Importance of Data Visualization

  2. 02

    Chapter 2: Getting Started with Our First Report

    • Setting Up Power BI Desktop • Data Importing Techniques • Creating Your First Report: Step-by-Step Tutorial

  3. 03

    Chapter 3: Data Modeling

    • Introduction to Data Modeling Concepts • Building Relationships between Tables • Best Practices for Data Modeling in Power BI

  4. 04

    Chapter 4: DAX Calculation

    • Understanding DAX (Data Analysis Expressions) • Creating Measures and Calculated Columns • Common DAX Functions

  5. 05

    Chapter 5: Data Cleaning and Transformation

    • Importance of Data Cleaning • Using Power Query for Data Transformation • Techniques for Handling Missing or Incorrect Data

  6. 06

    Chapter 6: Building Interactive Dashboards

    • Designing Effective Dashboards • Implementing Filters and Slicers • Utilizing Visual Elements for Enhanced User Experience

  7. 07

    Chapter 7: Additional Techniques

    • Advanced Visualization Techniques • Sharing and Collaborating in Power BI • Exploring Power BI Service and Mobile App Features

  8. 08

    Who Should Join?

    • Students interested in data analytics • Business professionals working with data • Aspiring BI or data analysts