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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:

Understanding business context, including organizational strategy and objectives
Creating custom data models that support analysis and reporting requirements
Identifying sources of data that can contribute to achieving business goals
Developing dashboards that provide actionable insights into business performance

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United States; USD 90,000
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Understanding Microsoft Power BI Data Analyst Certification Exam Topics

Microsoft Power BI Data Analyst Certification Exam Topics are below:

Deploy and maintain assets (20-25%)
Model the data (30-35%)
Prepare the data (15-20%)
Visualize and analyze the data (25-30%)

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

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Microsoft PL-300日本語 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Visualize and analyze data	25-30%	- Perform data analysis 1. Interpret results and identify trends 2. Create and manage bookmarks and tooltips 3. Implement custom visuals and R/Python scripts - Enhance reports with analytics 1. Use AI visuals, forecasts, and key influencers 2. Create paginated reports 3. Apply conditional formatting and custom visuals - 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
Topic 2: Manage and secure Power BI	15-20%	- 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. Embed content in applications or websites 2. Monitor usage and performance 3. Share reports, dashboards, and apps - Manage workspaces and assets 1. Manage data refresh and scheduled updates 2. Publish, update, and organize reports/datasets 3. Create and configure workspaces
Topic 3: Prepare the data	25-30%	- Load and configure data 1. Integrate data from multiple sources 2. Configure data refresh settings 3. Define table structures and properties - Get or connect to data 1. Identify and connect to data sources or shared semantic models 2. Create and modify parameters 3. Configure data source settings, credentials, and privacy levels 4. Choose storage modes: Import, DirectQuery, DirectLake - Profile and clean data 1. Manage data types, columns, and rows 2. Evaluate data statistics and column properties 3. Resolve inconsistencies, null values, and errors 4. Transform data using Power Query Editor
Topic 4: Model the data	25-30%	- Design data models 1. Create relationships: cardinality, cross-filter direction, security 2. Define tables, columns, and hierarchies 3. Implement role-playing dimensions 4. Create common date tables - Optimize model performance 1. Reduce cardinality and data size 2. Optimize relationships and calculations 3. Use aggregations and composite models - Create model calculations 1. Use DAX: calculated columns, calculated tables, measures 2. Use CALCULATE and filter context 3. Implement aggregation and time intelligence

Microsoft Power BI Data Analyst (PL-300日本語版) : PL-300日本語

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