Microsoft Power BI Data Analyst: PL-300 Certification Prep

A warm welcome to the Microsoft Power BI Data Analyst: PL-300 Certification Prep course by Uplatz.

The Microsoft PL-300 Exam (Power BI Data Analyst) is designed to validate the knowledge and skills required to analyze data using Power BI and deliver actionable insights.

Below are the key details of the exam:

Exam Details

• Exam Name: Microsoft Power BI Data Analyst

• Exam Code: PL-300

• Certification: Microsoft Certified: Power BI Data Analyst Associate

• Target Audience: Data Analysts, Business Intelligence Professionals, and Power BI Users

• Duration: 120 minutes (approximately)

• Passing Score: 700 (on a scale of 100-1000)

• Cost: $165 USD (varies by region)

Skills Measured

1. Prepare the Data (15–20%)

   • Connect to data sources and transform data using Power Query.

   • Clean, profile, and load data into Power BI.

   • Resolve errors and optimize data loading.

2. Model the Data (30–35%)

   • Design and develop data models.

   • Optimize model performance.

   • Define and implement calculations using DAX.

   • Create and manage hierarchies, relationships, and security settings.

3. Visualize and Analyze the Data (25–30%)

   • Create and customize visualizations.

   • Build dashboards and interactive reports.

   • Implement advanced analytics, such as key influencers and forecasting.

   • Optimize performance of visuals and dashboards.

4. Deploy and Maintain Assets (20–25%)

   • Publish and share Power BI reports and dashboards.

   • Manage workspace environments and user permissions.

   • Implement governance, security, and compliance in Power BI.

   • Integrate Power BI with other applications and platforms.

Exam Format

• Question Types:

  • Multiple Choice

  • Drag-and-Drop

  • Case Studies

  • Performance-based Labs (interactive simulations)

• Languages Available: English, Japanese, Simplified Chinese, German, and Spanish.

Ideal Candidates

• Professionals who use Power BI to transform raw data into meaningful insights.

• Individuals responsible for designing and building scalable data solutions for businesses.

• Data analysts looking to validate their Power BI expertise.

What is Power BI?

Microsoft Power BI is a business analytics tool that enables users to visualize data, share insights, and create interactive dashboards and reports. It allows businesses to analyze data from various sources and derive actionable insights for better decision-making. Power BI integrates with numerous data sources, providing a unified platform for data analysis and business intelligence.

How Power BI Works

1. Connect to Data Sources

   • Power BI can connect to a wide range of data sources, including Excel, SQL Server, Azure, SharePoint, cloud-based services, and APIs.

   • Use Power Query to clean, transform, and load data into the model.

2. Data Modeling

   • Create relationships between data tables and apply business rules.

   • Use DAX (Data Analysis Expressions) for custom calculations and measures.

3. Create Visualizations

   • Build interactive charts, graphs, and dashboards using drag-and-drop functionality.

   • Customize visuals to meet specific business requirements.

4. Share Insights

   • Publish dashboards and reports to the Power BI Service for collaboration.

   • Embed reports in websites, apps, or Microsoft Teams.

5. Real-time Analytics

   • Monitor real-time data from sources like IoT devices or streaming data feeds.

6. Governance and Security

   • Manage permissions, implement Row-Level Security (RLS), and ensure compliance with governance policies.

Key Features of Power BI

1. Ease of Use

   • User-friendly interface with drag-and-drop functionality and pre-built templates.

2. Wide Range of Data Connectors

   • Connect to over 100+ data sources, including databases, cloud services, APIs, and on-premises systems.

3. Powerful Data Transformation (Power Query)

   • Clean, merge, and transform raw data into a usable format without coding.

4. Advanced Data Modeling

   • Create complex relationships, hierarchies, and calculated measures using DAX.

5. Interactive Visualizations

   • Build dynamic reports with slicers, filters, and drill-through functionality.

6. AI-Powered Insights

   • Leverage features like key influencers, smart narratives, and machine learning integration for advanced analytics.

7. Collaboration and Sharing

   • Share reports via the Power BI Service, integrate with Microsoft Teams, and export to formats like PDF or Excel.

8. Mobile Reporting

   • Access and interact with reports on mobile devices using the Power BI Mobile app.

9. Real-time Data Analytics

   • Monitor and analyze streaming data in real-time for IoT applications and dashboards.

10. Integration with Microsoft Ecosystem

    • Seamlessly integrates with other Microsoft products like Excel, Azure, SharePoint, and Dynamics 365.

11. Power BI Embedded

    • Embed Power BI reports and dashboards into custom applications using Power BI Embedded.

12. Governance and Security

    • Supports Row-Level Security, Azure Active Directory integration, and compliance with industry standards like GDPR.

Why Use Power BI?

• For Business Users: Quickly create insights without deep technical knowledge.

• For Data Analysts and Engineers: Build complex models and derive advanced insights.

• For Enterprises: Centralize analytics, ensure data governance, and enable data-driven decision-making.

With its robust capabilities and integration within the Microsoft ecosystem, Power BI is a versatile tool suitable for organizations of all sizes.

Microsoft Power BI Data Analyst: PL-300 Certification Prep – Course Curriculum

Phase 1: Introduction to Data Analytics & Power Platform

Lecture 1 – Lecture 6

• Lecture 1: Introduction to Data Analytics

  • Overview of Data Analytics: History, importance, and applications

  • Roles in Data: Data Analyst, Data Engineer, Data Scientist, and Business Intelligence Developer

  • Latest Data Trends in 2024: Emerging technologies and their business impacts

• Lecture 2: Types of Data Analysis

  • Descriptive, Diagnostic, Predictive, and Prescriptive Analytics: Definitions and use cases

  • Data Sources: Structured, semi-structured, and unstructured data

  • Introduction to Big Data: Understanding its impact on analytics

• Lecture 3: Introduction to Power BI

  • What is Power BI: Overview and its role in modern data analytics

  • Power BI Architecture: Desktop, Service, Mobile, and Premium

  • Latest Features and Updates in Power BI (2024)

• Lecture 4: Introduction to Power Automate

  • Overview of Power Automate: Basics of workflow automation

  • Integrating Power Automate with Microsoft 365 Tools

  • Practical Use Cases of Power Automate in Business

• Lecture 5: Introduction to Power Apps and Dataverse

  • Power Apps: Creating low-code applications for businesses

  • Dataverse: Understanding its role in supporting the Power Platform

  • Connecting Power Apps to Dataverse and Building Scalable Apps

• Lecture 6: Introduction to Microsoft Fabric & Course Scope

  • What is Microsoft Fabric: Data governance and integration platform

  • Integration of Microsoft Fabric with Power BI and Power Platform

  • Scope of the Course: How the topics fit into broader data analytics and business solutions

Phase 2: Power BI – Data Preparation, Modeling, Visualization & Maintenance

Lecture 7 – Lecture 36

Module 1: Data Preparation

Lecture 7 – Lecture 11

• Connecting and cleaning raw data, handling missing values, advanced transformations using Power Query, and managing multiple data sources.

Module 2: Data Modeling

Lecture 12 – Lecture 16

• Star schema, relationships, advanced DAX calculations, managing data security with Row-Level Security (RLS).

Module 3: Data Visualization and Analysis

Lecture 17 – Lecture 27

• Building interactive visuals, implementing advanced analytics, creating KPIs and dashboards, optimizing performance, and exploring mobile reporting.

Module 4: Deployment and Maintenance

Lecture 28 – Lecture 36

• Deploying reports, administering Power BI, managing governance and security, exploring Power BI Premium, API integrations, and real-world use cases.

Phase 3: Power Platform Applications and Microsoft Fabric

Lecture 37 – Lecture 60

Module 1: Power Apps

Lecture 37 – Lecture 38

• Building and deploying apps, integrating with SharePoint and other data sources.

Module 2: Power Automate

Lecture 39 – Lecture 40

• Automating workflows, building advanced approvals, troubleshooting flows.

Module 3: Power Pages

Lecture 41 – Lecture 42

• Creating user-friendly websites, managing security, and embedding Power Apps.

Module 4: Microsoft Fabric

Lecture 43 – Lecture 44

• Understanding data pipelines, governance, and integrating with Power BI.

Module 5: Advanced Power Platform Use Cases

Lecture 45 – Lecture 56

• Multi-stage workflows, AI Builder, extending capabilities with custom connectors and Azure integrations.

Module 6: Real-World Projects and Exam Preparation

Lecture 57 – Lecture 60

• Solving case studies, practice exams, interview preparation, and exploring career opportunities.