Microsoft Power BI course
Utilizing custom visuals and importing them into Power BI.
Microsoft Power BI course
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Module 1: Introduction to Power BI
Understanding the role of Power BI in data visualization and analysis.
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Exploring the Power BI ecosystem: Desktop, Service, Mobile, and Gateway.
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Creating a Power BI account and navigating the Power BI interface.
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Connecting to various data sources: Excel, databases, online services, etc.
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Building a basic data visualization using Power BI Desktop.
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Module 2: Data Transformation and Modeling
Introduction to data transformation and cleaning techniques in Power Query.
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Importing and transforming data from different sources using Power Query.
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Data modeling concepts: relationships, cardinality, and direction.
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Creating calculated columns and measures using DAX (Data Analysis Expressions).
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Applying basic data modeling best practices to ensure efficient performance.
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Module 3: Data Visualization Fundamentals
Principles of effective data visualization and design.
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Creating and formatting various visualization types: bar charts, line charts, pie charts, etc.
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Enhancing visualizations with titles, legends, and annotations.
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Using slicers and filters for interactive data exploration.
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Building a dashboard with multiple visualizations and arranging them effectively.
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Module 4: Advanced Data Visualization Techniques
Utilizing custom visuals and importing them into Power BI.
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Implementing drill-through and drill-down functionalities.
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Working with map visualizations and geographical data.
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Creating hierarchical visualizations like treemaps and sunbursts.
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Designing interactive reports with bookmarks and tooltips.
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Module 5: Power BI Service and Collaboration
Uploading Power BI Desktop files to the Power BI Service.
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Sharing reports and dashboards with colleagues and stakeholders.
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Managing access and permissions for shared content.
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Collaborating on reports using comments and discussions.
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Setting up data refresh schedules to keep reports up to date.
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Module 6: Data Governance and Security
Introduction to data security considerations in Power BI.
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Implementing Row-Level Security (RLS) to restrict data access.
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Applying data classification and sensitivity labels to protect sensitive information.
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Auditing and monitoring activities within Power BI.
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Using the Power BI Admin Portal for managing workspace settings and usage metrics.
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Module 7: Advanced Data Modeling with DAX
Mastering more complex DAX functions and formulas.
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Understanding filter context and row context in DAX calculations.
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Time intelligence functions for analyzing trends and patterns.
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Working with calculated tables and table functions.
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Solving common business problems using advanced DAX techniques.
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Module 8: Performance Optimization
Identifying and resolving performance bottlenecks in Power BI reports.
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Techniques for optimizing data models and reducing file size.
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Using DirectQuery and Live Connection to enhance report performance.
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Best practices for efficient DAX coding and calculation optimization.
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Monitoring and improving report loading times.
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Module 9: Data Insights and AI Integration
Introduction to Power BI's AI capabilities and integration with Azure services.
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Creating machine learning models in Power BI using AutoML.
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Incorporating AI visuals like Key Influencers and Decomposition Tree.
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Natural Language Query (Q&A) for exploring data using conversational language.
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Building predictive analytics into reports using Power BI's AI features.
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Module 10: Advanced Visualization Customization
Customizing colors, themes, and styles for consistent branding.
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Using conditional formatting to highlight data points dynamically.
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Implementing custom tooltips and drill-through experiences.
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Creating custom visuals using tools like Power BI's API and Power Apps.
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Extending visualizations with HTML, JavaScript, and CSS for unique designs.
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Module 11: Real-time Data Streaming and Integration
Connecting Power BI to real-time data sources using streaming datasets.
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Building real-time dashboards to monitor dynamic data.
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Integrating Power BI with Azure Stream Analytics for complex streaming scenarios.
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Visualizing live data using custom visuals and real-time alerts.
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Designing effective real-time monitoring solutions for different industries.
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Module 12: Advanced Data Transformation and M Query
Deep dive into advanced data transformation techniques with M Query.
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Writing custom M code to handle complex data preparation tasks.
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Combining multiple queries and handling dependencies.
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Debugging and error handling in M Query.
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Practical examples of solving real-world data transformation challenges.
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Course Info
Data Visualization Basics
Introduction to data visualization principles
Creating basic visuals: tables, charts, maps, cards, etc.
Formatting visuals for clarity and aesthetics
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