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**AD-TEAM** · 02-01-2025, 08:20 PM

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Microsoft Power Bi Data Analyst: Pl-300 Certification Prep
Published 12/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 37.42 GB | Duration: 59h 20m

Build Power BI expertise. Learn Data Preparation, Modeling, Visualization, Deployment to ace the Microsoft PL-300 Exam.

What you'll learn

Prepare for the PL-300 Exam: Practice with mock exams and case studies tailored for the Microsoft Power BI Data Analyst certification.

Understand Data Analytics Foundations: Gain a comprehensive understanding of data analytics concepts, roles, and latest trends in the field.

Explore Types of Data Analysis: Learn the differences between descriptive, diagnostic, predictive, and prescriptive analytics and their practical applications.

Understand Power BI Architecture: Familiarize yourself with the components of Power BI, including Desktop, Service, Mobile, and Premium, and their integration.

Master Data Preparation Techniques: Connect to and transform raw data, handle missing values, and manage multiple data sources using Power Query.

Build Robust Data Models: Develop data models with star schemas, create relationships, and apply advanced DAX calculations for effective data analysis.

Enhance Data Security: Implement Row-Level Security (RLS) to manage and restrict data access.

Create Interactive Visualizations: Design engaging and interactive reports, dashboards, and KPIs that facilitate better decision-making.

Optimize Reporting Performance: Learn techniques to optimize Power BI reports for faster performance and scalability.

Explore Deployment and Maintenance: Deploy Power BI reports, manage governance and security, and leverage Power BI Premium and API integrations for enterprises.

Leverage the Power Platform Ecosystem: Understand the functionalities of Power Automate, Power Apps, Power Pages, and their integration with Power BI.

Understand Microsoft Fabric: Explore Microsoft Fabric's capabilities in data governance, pipelines, and integration with Power BI and the Power Platform.

Implement Advanced Power Platform Use Cases: Develop AI-enhanced workflows, multi-stage processes, and custom connectors for extended functionality.

Solve Real-World Case Studies: Apply acquired skills to real-world business scenarios, tackling complex data analytics problems.

Explore Career Opportunities: Discover data analytics career paths and prepare for roles like Data Analyst and Business Intelligence Developer.

Requirements

Enthusiasm and determination to make your mark on the world!

Description

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 DetailsExam Name: Microsoft Power BI Data AnalystExam Code: PL-300Certification: Microsoft Certified: Power BI Data Analyst AssociateTarget Audience: Data Analysts, Business Intelligence Professionals, and Power BI UsersDuration: 120 minutes (approximately)Passing Score: 700 (on a scale of 100-1000)Cost: $165 USD (varies by region)Skills MeasuredPrepare 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.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.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.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 FormatQuestion Types:Multiple ChoiceDrag-and-DropCase StudiesPerformance-based Labs (interactive simulations)Languages Available: English, Japanese, Simplified Chinese, German, and Spanish.Ideal CandidatesProfessionals 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 WorksConnect to Data SourcesPower 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.Data ModelingCreate relationships between data tables and apply business rules.Use DAX (Data Analysis Expressions) for custom calculations and measures.Create VisualizationsBuild interactive charts, graphs, and dashboards using drag-and-drop functionality.Customize visuals to meet specific business requirements.Share InsightsPublish dashboards and reports to the Power BI Service for collaboration.Embed reports in websites, apps, or Microsoft Teams.Real-time AnalyticsMonitor real-time data from sources like IoT devices or streaming data feeds.Governance and SecurityManage permissions, implement Row-Level Security (RLS), and ensure compliance with governance policies.Key Features of Power BIEase of UseUser-friendly interface with drag-and-drop functionality and pre-built templates.Wide Range of Data ConnectorsConnect to over 100+ data sources, including databases, cloud services, APIs, and on-premises systems.Powerful Data Transformation (Power Query)Clean, merge, and transform raw data into a usable format without coding.Advanced Data ModelingCreate complex relationships, hierarchies, and calculated measures using DAX.Interactive VisualizationsBuild dynamic reports with slicers, filters, and drill-through functionality.AI-Powered InsightsLeverage features like key influencers, smart narratives, and machine learning integration for advanced analytics.Collaboration and SharingShare reports via the Power BI Service, integrate with Microsoft Teams, and export to formats like PDF or Excel.Mobile ReportingAccess and interact with reports on mobile devices using the Power BI Mobile app.Real-time Data AnalyticsMonitor and analyze streaming data in real-time for IoT applications and dashboards.Integration with Microsoft EcosystemSeamlessly integrates with other Microsoft products like Excel, Azure, SharePoint, and Dynamics 365.Power BI EmbeddedEmbed Power BI reports and dashboards into custom applications using Power BI Embedded.Governance and SecuritySupports 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 CurriculumPhase 1: Introduction to Data Analytics & Power PlatformLecture 1 - Lecture 6Lecture 1: Introduction to Data AnalyticsOverview of Data Analytics: History, importance, and applicationsRoles in Data: Data Analyst, Data Engineer, Data Scientist, and Business Intelligence DeveloperLatest Data Trends in 2024: Emerging technologies and their business impactsLecture 2: Types of Data AnalysisDescriptive, Diagnostic, Predictive, and Prescriptive Analytics: Definitions and use casesData Sources: Structured, semi-structured, and unstructured dataIntroduction to Big Data: Understanding its impact on analyticsLecture 3: Introduction to Power BIWhat is Power BI: Overview and its role in modern data analyticsPower BI Architecture: Desktop, Service, Mobile, and PremiumLatest Features and Updates in Power BI (2024)Lecture 4: Introduction to Power AutomateOverview of Power Automate: Basics of workflow automationIntegrating Power Automate with Microsoft 365 ToolsPractical Use Cases of Power Automate in BusinessLecture 5: Introduction to Power Apps and DataversePower Apps: Creating low-code applications for businessesDataverse: Understanding its role in supporting the Power PlatformConnecting Power Apps to Dataverse and Building Scalable AppsLecture 6: Introduction to Microsoft Fabric & Course ScopeWhat is Microsoft Fabric: Data governance and integration platformIntegration of Microsoft Fabric with Power BI and Power PlatformScope of the Course: How the topics fit into broader data analytics and business solutionsPhase 2: Power BI - Data Preparation, Modeling, Visualization & MaintenanceLecture 7 - Lecture 36Module 1: Data PreparationLecture 7 - Lecture 11Connecting and cleaning raw data, handling missing values, advanced transformations using Power Query, and managing multiple data sources.Module 2: Data ModelingLecture 12 - Lecture 16Star schema, relationships, advanced DAX calculations, managing data security with Row-Level Security (RLS).Module 3: Data Visualization and AnalysisLecture 17 - Lecture 27Building interactive visuals, implementing advanced analytics, creating KPIs and dashboards, optimizing performance, and exploring mobile reporting.Module 4: Deployment and MaintenanceLecture 28 - Lecture 36Deploying 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 FabricLecture 37 - Lecture 60Module 1: Power AppsLecture 37 - Lecture 38Building and deploying apps, integrating with SharePoint and other data sources.Module 2: Power AutomateLecture 39 - Lecture 40Automating workflows, building advanced approvals, troubleshooting flows.Module 3: Power PagesLecture 41 - Lecture 42Creating user-friendly websites, managing security, and embedding Power Apps.Module 4: Microsoft FabricLecture 43 - Lecture 44Understanding data pipelines, governance, and integrating with Power BI.Module 5: Advanced Power Platform Use CasesLecture 45 - Lecture 56Multi-stage workflows, AI Builder, extending capabilities with custom connectors and Azure integrations.Module 6: Real-World Projects and Exam PreparationLecture 57 - Lecture 60Solving case studies, practice exams, interview preparation, and exploring career opportunities.

Overview

Section 1: Microsoft Power BI - Introduction to Data Analytics

Lecture 1 Microsoft Power BI - Introduction to Data Analytics

Section 2: Types of Data Analysis (PL-300 Focused)

Lecture 2 Types of Data Analysis (PL-300 Focused)

Section 3: Microsoft Power BI - Detailed Documentation

Lecture 3 Microsoft Power BI - Detailed Documentation

Section 4: Microsoft Power Automate

Lecture 4 Microsoft Power Automate

Section 5: Microsoft Power Apps and Microsoft Dataverse

Lecture 5 Microsoft Power Apps and Microsoft Dataverse

Section 6: Microsoft Fabric

Lecture 6 Microsoft Fabric

Section 7: Prepare the Data - Getting Started

Lecture 7 Prepare the Data - Getting Started

Section 8: Prepare the Data - Data Transformation

Lecture 8 Prepare the Data - Data Transformation

Section 9: Prepare the Data - Advanced Data Transformation

Lecture 9 Prepare the Data - Advanced Data Transformation

Section 10: Prepare the Data - Data Quality and Profiling (PL-300 Expert Guide)

Lecture 10 Prepare the Data - Data Quality and Profiling (PL-300 Expert Guide)

Section 11: Prepare the Data - Combining Data from Multiple Sources (PL-300 Expert Guide)

Lecture 11 Prepare the Data - Combining Data from Multiple Sources (PL-300 Expert Guide)

Section 12: Model the Data - Introduction to Data Modeling (PL-300 Expert Guide)

Lecture 12 Model the Data - Introduction to Data Modeling (PL-300 Expert Guide)

Section 13: Model the Data - Data Modeling Best Practices (PL-300 Expert Guide)

Lecture 13 Model the Data - Data Modeling Best Practices (PL-300 Expert Guide)

Section 14: Model the Data - Calculated Columns and Measures (PL-300 Expert Guide)

Lecture 14 Model the Data - Calculated Columns and Measures (PL-300 Expert Guide)

Section 15: Model the Data - Advanced DAX Calculations (PL-300 Expert Guide)

Lecture 15 Model the Data - Advanced DAX Calculations (PL-300 Expert Guide)

Section 16: Model the Data - Managing Data Security (PL-300 Expert Guide)

Lecture 16 Model the Data - Managing Data Security (PL-300 Expert Guide)

Section 17: Visualize and Analyze the Data - Introduction to Visuals (PL-300 Expert Guide)

Lecture 17 Visualize and Analyze the Data - Introduction to Visuals (PL-300 Expert Guide)

Section 18: Visualize and Analyze the Data - Advanced Visualizations (PL-300 Expert Guide)

Lecture 18 Visualize and Analyze the Data - Advanced Visualizations (PL-300 Expert Guide)

Section 19: Visualize and Analyze the Data - Visual Design Best Practices

Lecture 19 Visualize and Analyze the Data - Visual Design Best Practices

Section 20: Other Visualizations - Gauge Charts, KPI Cards, Maps

Lecture 20 Other Visualizations - Gauge Charts, KPI Cards, Maps

Section 21: Advanced DAX - Text Operators

Lecture 21 Advanced DAX - Text Operators

Section 22: Advanced DAX - Calculate, Filter, and All Functions

Lecture 22 Advanced DAX - Calculate, Filter, and All Functions

Section 23: Advanced DAX - Context Transition, Earlier, Variables

Lecture 23 Advanced DAX - Context Transition, Earlier, Variables

Section 24: Advanced DAX - Ranking, Cumulative Totals, Aggregations

Lecture 24 Advanced DAX - Ranking, Cumulative Totals, Aggregations

Section 25: Advanced DAX - Calculated Tables, Model Optimization, and Security

Lecture 25 Advanced DAX - Calculated Tables, Model Optimization, and Security

Section 26: Combo Charts and Area Charts in Power BI

Lecture 26 Part 1 - Combo Charts and Area Charts in Power BI

Lecture 27 Part 2 - Combo Charts and Area Charts in Power BI

Section 27: Scatter Plots and Bubble Charts

Lecture 28 Scatter Plots and Bubble Charts

Section 28: Ribbon Charts and Waterfall Charts

Lecture 29 Ribbon Charts and Waterfall Charts

Section 29: AI Visuals and AI Insights in Power BI

Lecture 30 AI Visuals and AI Insights in Power BI

Section 30: Latest Power BI Updates and New Visuals

Lecture 31 Latest Power BI Updates and New Visuals

Section 31: Performance Tuning for Visuals in Power BI

Lecture 32 Performance Tuning for Visuals in Power BI

Section 32: Tooltips, Bookmarks, and Drill Through

Lecture 33 Tooltips, Bookmarks, and Drill Through

Section 33: Power BI Themes and Layout Design

Lecture 34 Power BI Themes and Layout Design

Section 34: Real World Case Studies

Lecture 35 Real World Case Studies

Section 35: Power BI Interview Questions and Tips

Lecture 36 Power BI Interview Questions and Tips

Section 36: Introduction to Power BI Service

Lecture 37 Introduction to Power BI Service

Section 37: Managing Power BI Workspaces

Lecture 38 Managing Power BI Workspaces

Section 38: Power BI App Creation

Lecture 39 Power BI App Creation

Section 39: Power BI Premium Features

Lecture 40 Power BI Premium Features

Section 40: Case Studies in Power BI Service

Lecture 41 Case Studies in Power BI Service

Section 41: Power BI Security Essentials

Lecture 42 Power BI Security Essentials

Section 42: Rare Power BI Premium Features

Lecture 43 Rare Power BI Premium Features

Section 43: Power BI Gateways - Introduction and Setup

Lecture 44 Power BI Gateways - Introduction and Setup

Section 44: Advanced Power BI Premium and Data Automation

Lecture 45 Advanced Power BI Premium and Data Automation

Section 45: Advanced Embedding and Custom Integrations

Lecture 46 Advanced Embedding and Custom Integrations

Section 46: SQL Skills for Power BI Developers

Lecture 47 SQL Skills for Power BI Developers

Section 47: Advanced SQL and Databricks Integration

Lecture 48 Advanced SQL and Databricks Integration

Section 48: Data Transformation in Azure Databricks

Lecture 49 Data Transformation in Azure Databricks

Section 49: Data Analysis and Presentation using Excel

Lecture 50 Data Analysis and Presentation using Excel

Section 50: Cross-Functional Collaboration and Data Presentation

Lecture 51 Cross-Functional Collaboration and Data Presentation

Section 51: Stakeholder and Client Management

Lecture 52 Part 1 - Stakeholder and Client Management

Lecture 53 Part 2 - Stakeholder and Client Management

Section 52: Requirements Gathering and Analysis

Lecture 54 Requirements Gathering and Analysis

Section 53: Networking on LinkedIn and Personal Branding

Lecture 55 Networking on LinkedIn and Personal Branding

Section 54: Freelancing and Remote Job Opportunities

Lecture 56 Freelancing and Remote Job Opportunities

Section 55: Teaching Power BI and Building an Online Presence

Lecture 57 Teaching Power BI and Building an Online Presence

Section 56: Job Search Strategies and Interview Preparation

Lecture 58 Job Search Strategies and Interview Preparation

Section 57: Microsoft Fabric for Data Integration

Lecture 59 Microsoft Fabric for Data Integration

Section 58: Advanced Features in Microsoft Fabric

Lecture 60 Advanced Features in Microsoft Fabric

Section 59: Power Platform Essentials

Lecture 61 Power Platform Essentials

Section 60: Advanced Power Platform and Career Growth

Lecture 62 Advanced Power Platform and Career Growth

Aspiring Data Analysts preparing for the Microsoft PL-300 certification.,Professionals transitioning to data analytics or business intelligence roles.,Existing Power BI users seeking advanced skills in data modeling, visualization, and deployment.,IT and business professionals interested in leveraging the Power Platform ecosystem.,Data Scientists aiming to enhance their visualization and reporting skills.,Marketing Analysts seeking to derive insights and create impactful dashboards.,Data Consultants providing analytics and visualization solutions for clients.,Product Owners/Managers integrating data-driven insights into product strategies.,Team leaders or managers responsible for data-driven decision-making.,Students and graduates exploring a career in data analytics.,Developers and IT administrators integrating Power BI with enterprise systems.

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