Training Course: Analysis Using Excel and Power bi

Introduction

In today's data-driven world, businesses need to harness the power of data analysis to stay competitive and drive informed decision-making. Microsoft Excel and Power BI are among the most powerful tools available for performing comprehensive data analysis. This course is designed to equip participants with the most advanced techniques in data analysis using Excel and Power BI, ensuring they gain a thorough understanding of both tools for effective business data analysis. Whether you're looking to learn how to use Power BI for data analysis or master Excel's data modeling capabilities, this course will provide a complete overview.

Course Objectives

• Grasp the importance of data analysis for business decision-making and value creation.
• Learn how to use Excel and Power BI for advanced data analysis and business intelligence.
• Develop practical skills in data cleaning, transformation, and modeling using Excel and Power BI.
• Create powerful visualizations and interactive dashboards to communicate insights effectively.
• Apply predictive analysis techniques and real-world case studies to reinforce learning and practical application.

Course Outlines

Day 1: Introduction to Data Analysis with Excel and Power BI

• Overview of data analysis process and its significance in business decision-making.
• Introduction to data analysis using Excel and Power BI as essential tools for business insights.
• Exploring how to import data into Excel and Power BI, and the best practices for organizing and preparing data.
• Understanding the role of Power BI Analysis Services for building data models and analyzing large datasets.

Day 2: Data Cleaning and Transformation Techniques

• Understanding common data quality issues and techniques for effective data cleaning using Excel.
• Transforming data using Power Query in Excel and Power BI, including step-by-step demonstrations.
• Merging and appending data from various sources for comprehensive business data analysis.
• Exploring data analysis using Power BI, with an emphasis on best practices for data transformation and modeling.

Day 3: Data Modeling and Advanced Analysis

• An introduction to data modeling concepts, relationships between tables, and best practices for data structuring.
• Applying DAX (Data Analysis Expressions) in Excel and Power BI to create custom calculations and perform advanced analyses.
• Learning how to use Power BI for predictive analysis and building dynamic reports that support business forecasting.
• Discussing Power BI statistical analysis tools for more detailed insights into data patterns and trends.

Day 4: Advanced Visualization and Dashboard Creation

• Principles of effective data visualization for presenting insights clearly and persuasively.
• Step-by-step guidance on creating advanced charts, graphs, and visualizations in both Excel and Power BI.
• Building interactive dashboards that facilitate data exploration and help drive data-informed decisions.
• Exploring how to use Power BI for interactive data analysis projects and enhancing reports with advanced visualization tools.

Day 5: Applied Data Analysis and Case Studies

• Applying data analysis techniques to real-world business data analysis scenarios to ensure practical skill development.
• Hands-on exercises with case studies to enhance understanding and reinforce the practical application of course concepts.
• Leveraging insights from cost-benefit analysis using Excel and comparing it with predictive modeling and statistical analysis in Power BI.
• Final project: A comprehensive data analysis project using Power BI data analysis techniques to demonstrate acquired skills.

Conclusion

By the end of this course, participants will have a solid foundation in advanced data analysis using Excel and Power BI. They will be equipped to use Power BI for data analysis and perform comprehensive analyses with predictive modeling and statistical techniques. Participants will leave with a portfolio of Power BI data analysis projects and case study examples, enhancing their ability to apply business data analysis effectively in any professional setting.