Data Analysis with Microsoft Power BI

16 Weeks

All levels

25 lessons

0 quizzes

1 student

Overview
Curriculum
Instructor

Objective:

This learning module is designed to provide participants with a comprehensive understanding of data analysis using Microsoft Power BI Participants will learn how to leverage Power BI’s capabilities to transform raw data into actionable insights, create visually compelling reports and dashboards, and utilize advanced features for data analysis.

Assessment:

Quizzes, assignments, and practical exercises will be used to assess participants’ understanding of each module.

PROJECT

A final data analysis project using SPSS.
A final data analysis project using Excel.
A final project will be required for completion, showcasing the application of knowledge gained.

Final Defense and Graduation

Participants present their final data analysis projects.

b. Certificate of completion and graduation.

Curriculum

11 Sections
25 Lessons
16 Weeks

Expand all sectionsCollapse all sections

Module 1: Introduction to Data Analytics
3
Microsoft Power BI Installation and Setup
3
Module 2: Data Exploration & Hands-on Real Project
2
- 3.1
  a. Practical data exploration techniques.
- 3.2
  b. Real-world data analysis project kickoff.
Data Integration and Transformation
3
Module 3: Data Modeling and Relationships
2
- 5.1
  a. Building data models.
- 5.2
  b. Establishing relationships between datasets.
DAX (Data Analysis Expression)
2
- 6.1
  a. Introduction to DAX.
- 6.2
  b. Creating custom calculations and aggregations.
Feature Engineering & Data Measures
2
- 7.1
  a. Feature engineering principles.
- 7.2
  b. Creating data measures for analysis.
Module 4: Dashboard Design & Storytelling with Data
2
- 8.1
  a. Effective dashboard design.
- 8.2
  b. The art of storytelling through data visualization.
Publishing and Collaboration
2
- 9.1
  a. Publishing reports to the Power BI service.
- 9.2
  b. Collaboration and sharing using the Power BI service.
AI Capabilities in Power BI
2
- 10.1
  a. Exploring AI capabilities within Power BI.
- 10.2
  b. Leveraging machine learning and predictive analytics.
Module 5: Documentation and Portfolio Building
2
- 11.1
  a. Using GitHub repositories for documentation.
- 11.2
  b. Building a portfolio to showcase skills.

CHINEDU ODOH

Chinedu is an experienced data analyst with a passion for tech, blockchain, health and fintech. With three years of industry expertise and a talent for community growth. Over the past three years, He had the privilege of working alongside brilliant minds, harnessing the power of data and Low-code, No-code Microsoft tools to drive innovation and transformation in the ever-evolving tech landscape. With extensive experience thriving in collaborative and multidisciplinary environments, leveraging diverse perspectives to tackle complex challenges and drive innovative solutions, He has equipped stakeholders with a deep understanding of industry intricacies to successfully leverage data-driven insights to make a significant impact, optimizing operations and driving strategic decision-making. He's a Deputy city lead at Data scientist network/ Data Science Nigeria (DSN). Beyond analytical skills, He has actively contributed to growing communities and fostering collaboration among tech enthusiasts.

Data Analysis with Microsoft Power BI

Curriculum

CHINEDU ODOH

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