Mastering Data Analysis and Visualization with Microsoft Power BI

Overview:

Introduction:

Mastering data analysis and visualization with Microsoft Power BI involves leveraging this powerful tool to transform raw data into meaningful insights. Power BI enables users to connect, model, and visualize data efficiently, making it accessible to decision-makers through interactive dashboards and reports. This training program equips participants with the skills to analyze data, design compelling visualizations, and unlock the full potential of Microsoft Power BI for business intelligence and strategic decision-making.

Program Objectives:

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

• Gain proficiency in importing data into Microsoft Power BI.

• Create dynamic visualizations to interpret data effectively.

• Use Power BI features and functionality for insightful data analysis.

• Develop skills in generating actionable insights from datasets using Power BI.

• Enhance proficiency in making data-driven decisions through Power BI analysis.

Targeted Audience:

• Data analysts.

• Business intelligence professionals.

• Professionals seeking to enhance data visualization skills.

• Employees interested in leveraging Microsoft Power BI for data analysis.

Program Outlines:

Unit 1.

Introduction to Microsoft Power BI:

• Understanding the fundamentals of Microsoft Power BI.

• How to install and set up Microsoft Power BI.

• Exploring the user interface and workspace.

• The process of connecting to data sources.

• Navigating datasets and reports.

• Introduction to Power BI desktop and Power BI service.

Unit 2.

Data Import and Transformation:

• Importing data from various sources into Power BI.

• Cleaning and transforming data using Power Query Editor.

• Combining multiple data sources.

• How to handle data modeling and relationships.

• Calculated columns and measures.

• Introduction to DAX (Data Analysis Expressions).

Unit 3.

Creating Visualizations:

• The process of creating basic visualizations: charts and graphs.

• Customizing visualizations with formatting and design options.

• How to build interactive reports and dashboards.

• Incorporating slicers, filters, and drill-through functionality.

• Utilizing custom visuals and third-party integrations.

• Optimizing visualizations for performance.

Unit 4.

Advanced Analytics with Power BI:

• Advanced analytics techniques.

• Using time intelligence functions for date calculations.

• Processes involved in Performing statistical analysis and forecasting.

• Utilizing AI and machine learning capabilities.

• Dynamic insights with Q&A and natural language processing.

• Incorporating R and Python scripts for advanced analytics.

Unit 5.

Collaboration and Sharing:

• How to share reports and dashboards securely within organizations.

• Workspace collaboration features.

• Techniques of implementing row-level security and data protection measures.

• How to monitor and manage usage and performance metrics.