Mastering Data Analysis with Power BI

“Mastering Data Analysis with Power BI” is an advanced course designed to equip students with the skills and knowledge required to become proficient in using Microsoft Power BI for data analysis and visualization. This course delves into the intricacies of Power BI, focusing on data modeling, DAX (Data Analysis Expressions) language, and advanced visualization techniques. Participants will learn how to harness the power of Power BI to make data-driven decisions and produce insightful reports and dashboards.

Course Objectives:
  1. Advanced Data Modeling: Understand how to design and optimize data models in Power BI, including relationships, hierarchies, and advanced data transformations.
  2. DAX Mastery: Gain expertise in writing complex DAX formulas to perform calculations, create custom measures, and solve real-world data analysis challenges.
  3. Advanced Visualization: Learn to create interactive and compelling data visualizations, including custom visuals, drill-down/drill-through, and the use of themes.
  4. Data Integration: Explore data integration techniques, including data preparation, merging data from different sources, and transforming data for analysis.
  5. Real-World Applications: Apply Power BI to real-world data analysis scenarios, such as sales forecasting, financial analysis, and performance reporting.
  6. Power BI Service: Understand how to publish, share, and collaborate on Power BI reports using the Power BI service.
  7. Data Security: Learn about data security and governance best practices when working with sensitive data in Power BI.
  8. Optimization and Performance: Discover techniques to optimize data models and improve report performance.

Course Prerequisites:
  • Basic Power BI Knowledge
  • Data Analysis Background
  • Excel Skills
  • Basic Database Concepts

Target Audience:

 This course is intended for a range of professionals and students, including:
  • Data Analysts and Data Scientists
  • Business Intelligence Professionals
  • Business Professionals
  • IT Professionals
  • Students and Researchers

By the end of this course, participants will have the expertise to design complex data models, create advanced DAX formulas, and build interactive, insightful reports and dashboards using Power BI, enabling them to make data-driven decisions and solve complex business and analytical challenges.

Course Summary

Course Fee

৳ 15,000

Training Method

Offline/Online

Total Modules

7

Course Duration

72 Hours

Total Session

36

Class Duration

2 Hours

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Details Course Outlines - Mastering Data Analysis with Power BI

Module-01

Introduction to Data Analytics and PowerBI

  • Session 1: Understanding Data Analytics
  • 1.1 Introduction to Data Analytics
  • Definition and importance of data analytics.
  • Real-world examples of data-driven decisionmaking.
  • Data analytics lifecycle: from data collection to insights.
  • 1.2 Types of Data Analytics
  • Descriptive, diagnostic, predictive, and prescriptive analytics.
  • How different types of analytics are used in business.
  • Data analytics lifecycle: from data collection to insights.
  • Session 2: Introduction to PowerBI
  • 2.1 What is PowerBI
  • Overview of PowerBI as a business intelligence tool.
  • Key features and benefits of PowerBI.
  • 2.2 PowerBI Ecosystem
  • Different components of the PowerBI ecosystem (PowerBI Desktop, PowerBI Service, PowerBI Mobile).
  • Understanding the roles of each component in the analytics workflow.
  • Session 3: Installing and Setting Up PowerBI
  • 3.1 Installing PowerBI Desktop
  • Step-by-step installation guide for PowerBI Desktop.
  • System requirements and compatibility.
  • 3.2 Exploring PowerBI Interface
  • Introduction to the PowerBI Desktop user interface.
  • Navigating the Ribbon, Fields pane, and Data view.
  • Session 4: Overview of PowerBI Interface
  • 4.1 Workspace Overview
  • Understanding workspaces and files in PowerBI.
  • Creating and saving a new report.
  • 4.2 Connecting to Data Sources
  • Connecting to various data sources (Excel, databases, web, etc.).
  • Configuring data source settings.

Module-02

Data Preparation and Transformation

  • Session 1: Data Loading and Transformation
  • Session 1: Data Loading and Transformation
  • 2.1 Data Import in PowerBI
  • Review of various data sources (Excel, CSV, databases, web services, etc.) that can be connected to in PowerBI.
  • Step-by-step walkthrough of importing data.
  • 2.2 Data Profiling
  • Understanding the importance of data profiling in the data preparation process.
  • Identifying data quality issues and anomalies.
  • Session 2: Cleaning and Formatting Data
  • 2.3 Data Cleaning Techniques
  • Removing duplicates, handling missing values, and correcting data types.
  • Applying data transformations for data cleansing.
  • 2.4 Data Query Editor
  • Introduction to the Power Query Editor in PowerBI.
  • Using Power Query for advanced data cleaning and shaping.
  • Session 3: Combining Data from Multiple Sources
  • 2.5 Data Merging and Combining
  • Combining data from different sources using various merge options (join, append, etc.).
  • Creating relationships between tables.
  • 2.6 Data Transformations with DAX
  • Introduction to Data Analysis Expressions (DAX) for custom calculations.
  • Creating calculated columns.
  • Session 4: Data Modeling and Relationships
  • 2.7 Data Modeling in PowerBI
  • Understanding the concept of data modeling.
  • Defining relationships between tables (one-to-one, one-to-many, many-to-many).
  • 2.8 Creating Hierarchies
  • Building hierarchies for easier data exploration and drilling down.
  • Session 5-7: Creating Custom Columns and Measures
  • 2.9 Calculated Columns vs. Measures
  • Understanding the difference between calculated columns and measures.
  • When to use each.
  • 2.10 Writing DAX Formulas
  • Writing simple DAX formulas for creating custom columns and measures.
  • Using DAX functions for calculations.

Module-03

Data Visualization

  • Session 1: Introduction to Data Visualization
  • 3.1 Importance of Data Visualization
  • Understanding the role of data visualization in data analysis and storytelling.
  • Benefits of using visuals to convey insights.
  • 3.2 Types of Visualizations
  • Overview of common types of visualizations (bar charts, line charts, pie charts, etc.).
  • Choosing the right visualization for different data scenarios.
  • Session 2: Building Basic Visualizations
  • 3.3 Creating Charts and Graphs
  • Step-by-step guide to creating basic charts (bar charts, line charts, scatter plots, etc.) in PowerBI.
  • Data fields, values, and categories.
  • 3.4 Customizing Visualizations
  • Formatting options for visuals (color, fonts, labels, etc.).
  • Adding titles, legends, and data labels.
  • Session 3: Enhancing Visualizations with Filters and Slicers
  • 3.5 Using Filters
  • Applying filters to limit data displayed in visuals.
  • Utilizing filter types (visual-level, page-level, report-level).
  • 3.6 Slicers and Drill through
  • Creating slicers to allow user interaction.
  • Implementing drill through for deeper analysis.
  • Session 4: Creating Interactive Dashboards
  • 3.7 Building Dashboards
  • Understanding the concept of dashboards in PowerBI.
  • Adding visuals to dashboards and arranging them.
  • 3.8 Interactivity and Navigation
  • Making visuals interactive through cross-filtering and highlighting.
  • Creating navigation paths within dashboards.
  • Session 5: Drill-through and Drill-down Features
  • 3.9 Drill-through Pages
  • Creating drill-through pages for in-depth exploration.
  • Setting up drill-through actions.
  • 3.10 Drill-down Hierarchies
  • Creating drill-through pages for in-depth exploration.
  • Setting up drill-through actions.
  • Session 6&7: Advanced Visualization Techniques
  • 3.11 Advanced Chart Types
  • Exploring advanced chart types such as tree maps, gauges, and KPIs.
  • Use cases for each chart type.
  • 3.12 Data Storytelling
  • Principles of effective data storytelling.
  • Combining visuals and narratives for impactful presentations.

Module-04

Advanced Reporting

  • Session 1: Advanced Chart Types
  • 4.1 Gauges and KPIs
  • Introduction to gauges and Key Performance Indicators (KPIs).
  • Creating and customizing gauge visuals.
  • 4.2 Treemaps and Hierarchical Data
  • Understanding treemaps for hierarchical data visualization.
  • Building treemap visuals and using hierarchies.
  • Session 2: Using Hierarchies and Groups
  • 4.3 Hierarchy-Based Reporting
  • Leveraging hierarchies for drill-down and exploration.
  • Creating hierarchy slicers and visuals.
  • 4.4 Grouping Data
  • Grouping data for summarization and aggregation.
  • Applying grouping to visuals.
  • Session 3: Time Intelligence Functions
  • 4.5 Date and Time Functions
  • Introduction to date and time functions in PowerBI.
  • Calculating year-to-date, month-to-date, etc.
  • 4.6 Time-Based Visualizations
  • Creating time-based visuals like time lines and calendars.
  • Analyzing trends and patterns over time.
  • Session 4: Implementing Conditional Formatting
  • 4.7 Conditional Formatting Rules
  • Using conditional formatting to highlight data points.
  • Applying color scales, data bars, and icon sets.
  • 4.8 Dynamic Formatting with DAX
  • Using DAX expressions for conditional formatting.
  • Creating custom conditional formatting rules.
  • Session 5: Creating Custom Themes
  • 4.9 Custom Themes in PowerBI
  • Understanding the concept of custom themes.
  • Creating and applying custom themes to reports.
  • 4.10 Exporting and Sharing Themes
  • Exporting themes for use in other reports.
  • Sharing themes with team members.
  • Session 6: Advanced Analytics
  • 4.11 Statistical Analysis with PowerBI
  • Introduction to basic statistical functions in PowerBI
  • Conducting statistical analysis within reports.
  • 4.12 Python/R Integration
  • Overview of Python/R integration in PowerBI for advanced analytics.

Module-05

Data Sharing and Collaboration

  • Session 1: Publishing Reports to the Power BI Service
  • 5.1 Introduction to Power BI Service
  • Overview of Power BI Service and its role in sharing and collaboration.
  • Creating a Power BI Service account.
  • 5.2 Publishing Reports from Power BI Desktop
  • Step-by-step guide to publish reports from Power BI Desktop to Power BI Service.
  • Managing datasets and data sources.
  • Session 2: Configuring Security and Sharing Options
  • 5.3 Data Security in Power BI
  • Understanding role-based security in Power BI
  • Configuring security roles and permissions.
  • 5.4 Sharing and Collaboration
  • Sharing reports and dashboards with colleagues and stakeholders.
  • Collaborative editing and commenting.
  • Session 3: Creating and Managing Dashboards
  • 5.5 Building Dashboards in Power BI Service
  • Creating dashboards using visuals from published reports.
  • Customizing dashboard layouts.
  • 5.6 Real-time Dashboards
  • Setting up real-time data streaming for live dashboards.
  • Session 4: Exporting and Printing Reports
  • 5.7 Exporting Reports
  • Exporting reports in various formats (PDF, PowerPoint, Excel).
  • Customizing export settings.
  • Session 5: Power BI Mobile App
  • 5.8 Power BI Mobile App
  • Introduction to the Power BI mobile app.
  • Accessing and interacting with reports and dashboards on mobile devices.

Module-06

Real-World Projects and Case Studies

  • Session 1: Working on Real Data Analytics Projects
  • 6.1 Project Introduction
  • Overview of the real-world data analytics projects assigned for this module.
  • Explanation of project goals and objectives.
  • 6.2 Data Exploration and Preparation
  • Reviewing the provided datasets and understanding data requirements.
  • Cleaning and preparing data for analysis.
  • Session 2: Solving Data Analysis Challenges
  • 6.3 Data Analysis Techniques
  • Applying data analysis techniques to the project datasets.
  • Identifying patterns, trends, and insights.
  • 6.4 Troubleshooting and Problem-Solving
  • Addressing challenges and issues encountered during data analysis.
  • Debugging and refining analysis processes.
  • Session 3: Presenting Findings and Insights
  • 6.5 Creating Comprehensive Reports
  • Building reports and dashboards based on project findings.
  • Visualizing insights effectively
  • 6.6 Data Storytelling and Communication
  • Developing a narrative around the analysis results.
  • Preparing for project presentations.
  • Session 4: Peer Review and Feedback
  • 6.7 Peer Review Process
  • Peer review of each other's project reports and dashboards.
  • Providing constructive feedback and suggestions for improvement.
  • 6.8 Iteration and Refinement
  • Making improvements based on peer feedback.
  • Revising project reports and presentations.
  • Session 5&6: Final Presentation and Conclusion
  • 6.9 Final Project Presentation
  • Participants present their project findings, insights, and visualizations to the class.
  • Q&A session and discussions.
  • 6.10 Course Conclusion
  • Review of key takeaways and lessons learned throughout the course.
  • Distribution of course completion certificates.

Module-07

Final Assessment and Certification

  • Final Assessment Exam
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