Data Analysis Using Power BI Fundamentals

12 Feb 2026

220 $

Data Analysis Using Power BI Fundamentals

Brief

Data has become a core asset for organizations, playing a critical role in operational efficiency, performance measurement, and decision-making. The Data Analysis (Power BI) program is designed to provide a structured and practical foundation in data analysis from a business-focused perspective. The program covers the full data analysis workflow, starting with raw data, moving through data cleaning and preparation, basic data modelling, and concluding with the creation of KPIs, reports,

Start Date

12 Feb 2026

Lessons

6

Time

24 Hours

Course Level

Intermediate

The training emphasizes developing analytical thinking and understanding how business requirements are translated into data models and interactive reports. Participants receive practical experience using Power BI to build KPI-driven dashboards, explore data through filters and relationships, and interpret results within a real business context, without requiring advanced programming or technical backgrounds.

What You Will Learn:

By the end of the program, participants will be able to:

Understand the concept of data analysis and its role in business decision-making.
Import data into Power BI from Excel and CSV files.
Understand data structure correctly (rows, columns, and tables).
Clean and prepare data using Power Query.
Create basic relationships between tables.
Build basic calculations and Key Performance Indicators (KPIs) using DAX.
Create clear tables, charts, and visual reports.
Use filters and slicers to explore and analyze data.
Design a simple interactive dashboard step by step.
Read reports and interpret results to extract insights that support decision-making.

Program Summary:

Beginner-friendly training program with no technical background required.
Focuses on the foundations of data analysis using Power BI.
Teaches how to move from raw data to a clear & interactive dashboard.
Emphasizes practical understanding and step-by-step application.
Includes practical exercises using real-world data examples.
Ideal for individuals starting their career path in data analysis.

Course Content

What data is and what data analysis means in simple business terms. - How organizations use data to support decisions. - The role of data analysis in performance improvement.

What Power BI is and where it is commonly used. - Overview of the Power BI ecosystem (Desktop & Service).

Importing data from Excel and CSV files. - Understanding tables and fields within Power BI. - Data types (text, numeric, date). - Previewing and reviewing data before analysis.

Rows, columns, and tables. - Best practices for organizing data correctly.

What Power Query is and why it matters. - Removing blank rows and duplicates. - Correcting data types and formats. - Renaming and organizing columns, applying filters and sorting. - Preparing clean, analysis-ready datasets.

What a data model is (simplified explanation). - Creating basic relationships between tables. - Understanding how relationships affect analysis results.

What DAX is and why it is used. - Difference between calculated columns and measures. - Creating basic calculations such as: Total Sales & Record Count - Understanding how filters impact calculations.

Types of charts and tables available in Power BI. - Selecting the appropriate visual for each analytical question. - Creating basic charts and tables. - Formatting reports for clarity and readability.

Using filters and slicers to explore data. - Combining reports into a single dashboard. - Building an interactive dashboard step by step.

Reading and interpreting reports. - Identifying basic trends and patterns.

Instructors

Youssef Hassan

Youssef Hassan, a marketing manager and instructor, has been endowed with over 13 years of experience in marketing and digital marketing. Throughout this period, work has been carried out with leading global, Arab, and Egyptian brands, including Ford, Hyper Panda, Panasonic, Ariston, Lincoln, and Burger King, as well as numerous companies across more than 60 diverse sectors.