Course Prerequisites
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Participants looking to take up the Microsoft Power BI Data Analyst PL-300 training should have at least 1-2 years of professional experience using Microsoft Windows and related products.
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If the candidate is new to cloud and Azure, then AZ-900: Microsoft Azure Fundamentals training is strongly recommended.
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If the candidate is new in managing data solutions or Azure, then DP-900: Microsoft Azure Data Fundamentals training is recommended
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If the candidate is looking to evolve their skills on Microsoft Power Platform, then PL-900: Microsoft Power Platform Fundamentals training is recommended but not mandatory

Microsoft Power BI Data Analyst (PL 300) Certification Training Course
In today’s evolving business landscape, for organizations to stay relevant and competitive, it is critical to embrace cloud solutions such as Azure to ensure business continuity at all costs. With data analysis becoming one of the critical processes in enterprises across industry sectors, it is imperative for enterprises to utilize untapped data assets spread across physical, cloud, and hybrid environments.
Microsoft went ahead and changed their ever-popular DA-100 training program to stay relevant to the evolving needs of the market and renamed it to PL-300 Microsoft Power BI Data Analyst training. Through this PL-300 training, participants will gain complete knowledge of driving business value through data visualizations that are easy to understand and help other stakeholders to perform self-service analytics, configure, and deploy solutions for consumption.
Reasons to choose Koenig Solutions’ Microsoft Power BI Data Analyst PL-300 Training
Widely-acknowledged PL 300 certification training delivered with Expert Microsoft Instructor
Gain a complete understanding of analyzing data assets through Microsoft Power BI through this PL-300 training
Expert Power BI instructors and hands-on labs to clear your PL 300 examination
Expand the scope of your career as a Microsoft Certified: Data Analyst Associate
Get a chance to join with other interested individuals belonging to various industry sectors and understand how data analysis is performed
Key Features of PL 300 Training Course
Instructor-led Microsoft Power BI Data Analyst PL-300 Training
Get access to a free 1-hour PL-300 course preview to learn Microsoft Power BI concepts
Expert Microsoft Power BI instructors across the globe
Accredited Microsoft PL-300 course material prepared by SMEs
Get real-life experience through Microsoft lab sessions
Industry-recognized PL-300 Course Completion certificate provided
PL-300 training provided across 100+ locations globally
Who can take up Microsoft Power BI Data Analyst (PL-300) Training?
Job roles that can take up Microsoft Power BI Data Analyst Training include, but are not limited to:
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Business Intelligence Professionals
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Data analysts
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IT Managers
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Professionals who use Power BI
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Data Scientists
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Professionals Managing Data for Decision-making
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Individuals who want to gain a clear understanding of the Microsoft Power BI Tool
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Professionals who want to clear the Microsoft Power BI Data Analyst PL-300 examination
Learning Objectives of PL-300 Microsoft Power BI Data Analyst Training
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Participants taking part in this PL-300 certification training will learn about:
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Ingesting, cleaning, and transforming data
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Modeling data for performance and scalability
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Designing and creating reports for data analysis
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Applying and performing advanced report analytics
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Managing and sharing report assets
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Creating paginated reports in Power BI
Microsoft Power BI Data Analyst PL-300 Exam Format
Exam Name
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Microsoft PL-300
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Certification Name
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Microsoft Certified: Data Analyst Associate
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PL 300 Exam Type
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Multiple-choice and Multiple response questions
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PL 300 Exam Cost
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USD 165.00*
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Total Questions
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40 – 60 Questions
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PL-300 Exam Duration
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180 Minutes
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Languages
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English, Japanese, Chinese (Simplified), and Korean
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Microsoft Power BI Data Analyst PL-300 Course Outline
Participants who take up PL-300 Certification Course will learn about:
Prepare the Data (15-20%)
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Getting data from different data sources
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Cleaning, transforming, and loading the data
Model the Data (30-35%)
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Designing a data model
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Developing a data model
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Creating model calculations by using DAX
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Optimizing model performance
Visualize and Analyze the Data (25-30%)
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Creating reports
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Creating dashboards
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Enhancing reports for usability and storytelling
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Identifying patterns and trends
Deploy and Maintain Assets (20-25%)
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Managing files and datasets
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Managing workspaces