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Microsoft PL-300 exam is intended for individuals who are data analysts, business analysts, or data professionals who specialize in data analysis and visualization. PL-300J exam is also suitable for IT professionals who want to enhance their skills in data analysis and visualization using Microsoft Power BI. PL-300J exam requires candidates to have a solid understanding of data modeling, data visualization, and data analysis concepts, as well as experience working with Power BI tools.

Earning the Microsoft PL-300 Certification can provide various benefits to professionals, including increased job opportunities, higher salaries, and greater recognition from peers and employers. Microsoft Power BI Data Analyst (PL-300日本語版) certification can also help professionals improve their skills in Power BI, enabling them to create more impactful and effective visualizations and reports. Overall, the Microsoft PL-300 Certification Exam is an excellent way for professionals to demonstrate their expertise in Power BI and advance their careers in the field of data analytics.

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What are the special features of the Microsoft Power BI Data Analyst Certification Exam

The Microsoft Power BI Data Analyst Certification Exam will help you prepare for the new job role of a data analyst. A certified Data Analyst can use this exam to prove their skills in using Power BI to analyze business data, generate insightful visualizations, and share them with customers. Microsoft PL-300 Dumps is designed to test your knowledge of business data modeling, data analysis and visualization, and dashboard development in Power BI. The exam will cover the following topics:

  • Identifying sources of data that can contribute to achieving business goals

  • Understanding business context, including organizational strategy and objectives

  • Developing dashboards that provide actionable insights into business performance

  • Creating custom data models that support analysis and reporting requirements

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300

Passing the Microsoft PL-300 certification exam demonstrates that an individual has the skills and knowledge required to work with Power BI effectively. It is also an excellent way to showcase one's expertise in data analysis and visualization to potential employers. Microsoft Power BI Data Analyst (PL-300日本語版) certification can help individuals stand out in a competitive job market and can lead to new job opportunities and career growth.

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Microsoft PL-300日本語 Exam Syllabus Topics:

SectionWeightObjectives
Visualize and analyze data25-30%- Perform data analysis
  • 1. Interpret results and identify trends
    • 2. Create and manage bookmarks and tooltips
      • 3. Implement custom visuals and R/Python scripts
        - Create reports and dashboards
        • 1. Apply filters, slicers, and drill-through
          • 2. Choose appropriate visualizations
            • 3. Create dashboards and pinned elements
              • 4. Design report layout, formatting, and interactivity
                - Enhance reports with analytics
                • 1. Use AI visuals, forecasts, and key influencers
                  • 2. Create paginated reports
                    • 3. Apply conditional formatting and custom visuals
                      Manage and secure Power BI15-20%- Manage workspaces and assets
                      • 1. Publish, update, and organize reports/datasets
                        • 2. Manage data refresh and scheduled updates
                          • 3. Create and configure workspaces
                            - Implement security and governance
                            • 1. Apply data sensitivity labels and protection
                              • 2. Configure row-level security (RLS) and object-level security
                                • 3. Manage permissions and access
                                  - Deploy and distribute content
                                  • 1. Monitor usage and performance
                                    • 2. Share reports, dashboards, and apps
                                      • 3. Embed content in applications or websites
                                        Model the data25-30%- Create model calculations
                                        • 1. Use CALCULATE and filter context
                                          • 2. Use DAX: calculated columns, calculated tables, measures
                                            • 3. Implement aggregation and time intelligence
                                              - Design data models
                                              • 1. Define tables, columns, and hierarchies
                                                • 2. Implement role-playing dimensions
                                                  • 3. Create common date tables
                                                    • 4. Create relationships: cardinality, cross-filter direction, security
                                                      - Optimize model performance
                                                      • 1. Optimize relationships and calculations
                                                        • 2. Reduce cardinality and data size
                                                          • 3. Use aggregations and composite models
                                                            Prepare the data25-30%- Get or connect to data
                                                            • 1. Configure data source settings, credentials, and privacy levels
                                                              • 2. Create and modify parameters
                                                                • 3. Choose storage modes: Import, DirectQuery, DirectLake
                                                                  • 4. Identify and connect to data sources or shared semantic models
                                                                    - Load and configure data
                                                                    • 1. Configure data refresh settings
                                                                      • 2. Integrate data from multiple sources
                                                                        • 3. Define table structures and properties
                                                                          - Profile and clean data
                                                                          • 1. Evaluate data statistics and column properties
                                                                            • 2. Resolve inconsistencies, null values, and errors
                                                                              • 3. Manage data types, columns, and rows
                                                                                • 4. Transform data using Power Query Editor

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