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Microsoft PL-300 Korean Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Power BI Data Analyst |
| Exam Number: | PL-300 |
| Certificate Validity Period: | 1 year (renewable annually via Microsoft Learn assessment) |
| Passing Score: | 700 (out of 1000) |
| Exam Price: | USD $165 (varies by country/region) |
| Exam Format: | Multiple choice, Drag and drop, Case studies, Lab simulations, Multiple response |
| Related Certifications: | Microsoft Certified: Data Analyst Associate Microsoft Certified: Power Platform Fundamentals (PL-900) |
| Available Languages: | Chinese (Simplified), French, English, Korean, Spanish, Japanese, Portuguese (Brazil), Italian, German |
| Exam Duration: | 100-120 |
| Real Exam Qty: | 40-60 (approx.) |
| Recommended Training: | Power BI Guided Learning Microsoft Learn PL-300 Learning Path |
| Exam Registration: | Pearson VUE Registration Microsoft Certification Portal |
| Sample Questions: | Microsoft PL-300 Korean Sample Questions |
| Exam Way: | Online proctored exam or onsite test center via Pearson VUE |
| Pre Condition: | No mandatory prerequisites, but recommended: 1+ year experience with Power BI and data analysis. |
| Official Syllabus URL: | https://learn.microsoft.com/credentials/certifications/power-bi-data-analyst-associate/ |
Microsoft PL-300 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Prepare the Data (15-20%) | |
| Get data from different data sources | - identify and connect to a data source - change data source settings - select a shared dataset or create a local dataset - select a storage mode - use Microsoft Dataverse - change the value in a parameter - connect to a data flow |
| Clean, transform, and load the data | - profile the data - resolve inconsistencies, unexpected or null values, and data quality issues - identify and create appropriate keys for joins - evaluate and transform column data types - shape and transform tables - combine queries - apply user-friendly naming conventions to columns and queries - configure data loading - resolve data import errors |
Model the Data (30-35%) | |
| Design a data model | - define the tables - configure table and column properties - design and implement role-playing dimensions - define a relationship's cardinality and cross-filter direction - design a data model that uses a star schema - create a common date table |
| Develop a data model | - create calculated tables - create hierarchies - create calculated columns - implement row-level security roles - use the Q&A feature |
| Create model calculations by using DAX | - create basic measures by using DAX - use CALCULATE to manipulate filters - implement Time Intelligence using DAX - replace implicit measures with explicit measures - use basic statistical functions - create semi-additive measures - use quick measures |
| Optimize model performance | - remove unnecessary rows and columns - identify poorly performing measures, relationships, and visuals - reduce cardinality levels to improve performance |
Visualize and Analyze the Data (25-30%) | |
| Create reports | - add visualization items to reports - choose an appropriate visualization type - format and configure visualizations - use a custom visual - apply and customize a theme - configure conditional formatting - apply slicing and filtering - configure the report page - use the Analyze in Excel feature - choose when to use a paginated report |
| Create dashboards | - manage tiles on a dashboard - configure mobile view - use the Q&A feature - add a Quick Insights result to a dashboard - apply a dashboard theme - pin a live report page to a dashboard |
| Enhance reports for usability and storytelling | - configure bookmarks - create custom tooltips - edit and configure interactions between visuals - configure navigation for a report - apply sorting - configure Sync Slicers - group and layer visuals by using the selection pane - drilldown into data using interactive visuals - export report data - design reports for mobile devices |
| Identify patterns and trends | - use the Analyze feature in Power BI - identify outliers - choose between continuous and categorical axes - use groupings, binnings, and clustering - use AI visuals - use the Forecast feature - create reference lines by using the Analytics pane |
Deploy and Maintain Assets (20-25%) | |
| Manage files and datasets | - identify when a gateway is required - configure a dataset scheduled refresh - configure row-level security group membership - provide access to datasets - manage global options for files |
| Manage workspaces | - create and configure a workspace - assign workspace roles - configure and update a workspace app - publish, import, or update assets in a workspace - apply sensitivity labels to workspace content - configure subscriptions and data alerts - promote or certify Power BI content |
Exam PL-300: Microsoft Power BI Data Analyst
The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.
Passing score: 700. Learn more about exam scores.
- Download the PL-300 study guide to help you prepare for the exam
- Demo the exam experience by visiting our Exam Sandbox
- Watch PL-300 Exam Prep videos on Learn
Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
By Bertha
