Power BI (PL-300 Compliant)

PL-300: Microsoft Power BI Data Analyst - Training Syllabus

1. Prepare Data (15-20%)
  • Introduction to Power BI
    • Overview of Power BI Desktop and Power BI Service
    • Power BI architecture and components
  • Get Data from Different Sources
    • Importing data from various data sources (Excel, SQL Server, SharePoint, Web, API)
    • Connecting to cloud data sources (Azure, Salesforce)
    • Import vs Direct Query vs Live Connection
  • Clean, Transform, and Load Data
    • Using Power Query Editor for data cleaning
    • Removing duplicates, filtering, sorting data
    • Transforming data (pivot, unpivot, aggregating)
    • Fixing data types, data merging, appending queries
    • Conditional columns, custom columns
    • Understanding data model vs. report data
2. Model Data (30-35%)
  • Design and Create a Data Model
    • Understanding relationships: one-to-one, one-to-many, many-to-many
    • Data modeling concepts: Star and Snowflake schema
    • Using primary and foreign keys, normalizing data
  • Create Calculations in Data Model
    • Introduction to DAX (Data Analysis Expressions)
    • Creating calculated columns, measures, and calculated tables
    • Aggregation functions, logical functions, and time intelligence
    • Working with different types of filters in DAX
    • Building row-level security (RLS) for role-based access
  • Optimize Data Model
    • Improving performance with indexing, data type management
    • Handling large datasets and improving query performance
3. Visualize and Analyze Data (25-30%)
  • Creating Reports and Dashboards
    • Overview of Power BI visuals (charts, tables, KPIs, maps, etc.)
    • Customizing visuals: Colors, themes, labels, and conditional formatting
    • Building reports and interactive dashboards
    • Using slicers, filters, and drill-throughs for interactivity
  • Advanced Visualizations
    • Using AI visuals for predictive modeling (Key Influencers, Decomposition Tree)
    • Trend lines, clustering, and forecasting visuals
    • Using Power BI visuals (R, Python scripts) for advanced analysis
  • Enhanced Data Analysis
    • Implementing quick measures for insights
    • Adding dynamic parameters (What-If analysis)
    • Customizing tooltips and creating custom visuals
    • Setting up alerts and notifications for important metrics
4. Deploy and Maintain Assets (20-25%)
  • Managing Workspaces and Datasets
    • Publishing Power BI reports and dashboards to the Power BI Service
    • Creating and managing workspaces for collaboration
    • Configuring and managing datasets in the Power BI Service
  • Data Refresh and Security
    • Setting up automatic data refreshes (scheduled refresh, on-demand refresh)
    • Troubleshooting refresh errors and configurations
    • Role-based security (RLS) and dataset permissions
  • Publishing and Sharing Reports
    • Sharing reports and dashboards with stakeholders
    • Embedding Power BI reports in websites, SharePoint, and Teams
    • Creating Power BI apps for distributing reports to users
5. Interview Preparation and Real-World Applications (Additional)
  • Interview-Ready Questions
    • Sample interview questions based on PL-300 syllabus
    • Mock interviews and problem-solving sessions
  • Real-World Projects
    • Students will work on a real-world Power BI project using datasets from various domains like sales, finance, or marketing
    • Implementing data cleaning, model design, and visualizations from scratch
  • Resume Building and Job Assistance
    • Tips for building a strong Power BI-focused resume
    • Job roles: Data Analyst, BI Developer, and Power BI Specialist
6. Final Project and Certification Preparation
  • Final Project
    • End-to-end Power BI project with clean data, a well-designed data model, and meaningful visualizations
  • PL-300 Certification Tips
    • Understanding the exam structure and key concepts
    • Practice tests and exam preparation tips