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Microsoft PL-300 Deutsch Actual Tests : Microsoft Power BI Data Analyst (PL-300 Deutsch Version)

PL-300 Deutsch actual test
  • Exam Code: PL-300-Deutsch
  • Exam Name: Microsoft Power BI Data Analyst (PL-300 Deutsch Version)
  • Updated: Nov 05, 2026
  • Q & A: 472 Questions and Answers
  • PDF Demo
  • PC Test Engine
  • Online Test Engine
  • Total Price: $69.99  

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Microsoft Power BI Data Analyst Exam Certification Details:

Exam Price$165 (USD)
Books / TrainingCourse PL-300T00: Microsoft Power BI Data Analyst
Sample QuestionsMicrosoft Power BI Data Analyst Sample Questions
Exam CodePL-300
Schedule ExamPearson VUE
Passing Score700 / 1000
Exam NameMicrosoft Certified - Power BI Data Analyst Associate
Duration180 mins
Number of Questions40-60

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

Passing Score, Duration & Questions For Microsoft PL-300 Exam

  • Languages: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian

  • Number of Questions: 40-60 questions

  • The passing score: 700

  • Time Duration: 180 minutes

Microsoft PL-300 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Analyze the Data10-15%- Perform analysis in Power BI
  • 1. Use the Q&A visual
  • 2. Apply Quick Insights
  • 3. Identify patterns and trends
  • 4. Generate Pinn visual insights
  • 5. Configure auto-insights
- Work with metrics in Power BI
  • 1. Use the Decomposition Tree visual
  • 2. Create metrics using Microsoft measurements
  • 3. Track goals with scorecards
  • 4. Define and monitor KPIs
Topic 2: Prepare the Data10-15%- Get data from various data sources
  • 1. Choose between DirectQuery, Import, and Dual storage modes
  • 2. Use Microsoft Fabric and OneLake
  • 3. Configure dataset refresh
  • 4. Select a shared dataset or create a local copy
  • 5. Change data source settings
  • 6. Identify and connect to a data source
- Clean, transform, and load the data
  • 1. Apply user-friendly naming conventions to columns and tables
  • 2. Determine proper data types
  • 3. Profile the data
  • 4. Configure data loading and queries
  • 5. Design and build intermediate tables
  • 6. Resolve data quality issues
  • 7. Identify the data structure
Topic 3: Model the Data25-30%- Develop the data model
  • 1. Create calculated tables and columns
  • 2. Use the calculation group feature
  • 3. Build hierarchies and hierarchical fields
  • 4. Configure table relationships
  • 5. Create common date tables
  • 6. Implement row-level security roles
- Design a data model
  • 1. Define tables and table schemas
  • 2. Design a star schema or snowflake schema
  • 3. Determine the appropriate granularity
  • 4. Apply field metadata and groupings
  • 5. Resolve performance issues with relationships
  • 6. Implement row-level security
- Create measures and DAX calculations
  • 1. Write and use basic DAX syntax
  • 2. Use Time Intelligence functions
  • 3. Create calculated measures
  • 4. Create semi-additive measures
  • 5. Use CALCULATE and FILTER functions
  • 6. Implement context transition
- Optimize model performance
  • 1. Optimize Dax queries
  • 2. Validate performance and resolve issues
  • 3. Optimize DirectQuery models
  • 4. Configure aggregations
  • 5. Improve user experience by hiding objects
Topic 4: Manage and Maintain Workspace Items10-15%- Create and manage workspaces
  • 1. Endorse sensitive content with sensitivity labels
  • 2. Configure workspace membership and roles
  • 3. Publish and update a Power BI app
  • 4. Configure content certification
- Manage datasets
  • 1. Configure dataset metadata and properties
  • 2. Resolve dataset permission issues
  • 3. Manage gateways and data sources
  • 4. Manage dataset refresh scheduling
Topic 5: Visualize the Data25-30%- Build visuals
  • 1. Determine the appropriate visual type
  • 2. Format and configure pages and report backgrounds
  • 3. Configure data colors and shapes
  • 4. Apply sorting and filtering to visuals
  • 5. Configure visual interactions and cross-filtering
  • 6. Apply AI insights and enhanced analytics
- Enhance reports for user experience
  • 1. Design for mobile and specific layouts
  • 2. Add accessibility features and compliance
  • 3. Apply artistic formatting to visuals
  • 4. Add tooltips and navigation
- Enrich reports with advanced visuals
  • 1. Create custom visuals
  • 2. Configure R and Python visuals
  • 3. Use dynamic page navigation
  • 4. Integrate Microsoft Copilot for Power BI

Microsoft Power BI Data Analyst (PL-300 Deutsch Version) Sample Questions:

Question #1

Sie müssen das Datenmodell so gestalten, dass es den Berichtsanforderungen entspricht.
Was sollten Sie in Power BI Desktop tun?

  • A. Verwenden Sie in Power Query einen DAX-Ausdruck, um der Tabelle „Orders“ Spalten hinzuzufügen, mit denen das Kalenderquartal der Spalte „OrderDate“, der Kalendermonat der Spalte „OrderDate“, das Kalenderquartal der Spalte „ShippedDate“ und der Kalendermonat der Spalte „ShippedDate“ berechnet werden können.
  • B. Fügen Sie mithilfe von Power Query Spalten zur Tabelle „Bestellungen“ hinzu, um das Kalenderquartal und den Kalendermonat der Spalte „Bestelldatum“ zu berechnen.
  • C. Fügen Sie in Power Query eine Datumstabelle hinzu. Erstellen Sie eine aktive Beziehung zur Spalte „OrderDate“ in der Tabelle „Orders“ und eine inaktive Beziehung zur Spalte „ShippedDate“ in der Tabelle „Orders“.
  • D. Verwenden Sie in Power BI Desktop die Option „Automatische Datums-/Zeitangabe“ beim Erstellen der Berichte.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #2

Sie erstellen ein semantisches Modell aus einer JSON-Datei, die ein Array von Dokumenten enthält.
Sie müssen Attribute als Spalten aus allen Dokumenten der JSON-Datei importieren. Die Lösung muss sicherstellen, dass Datumsattribute in Microsoft Power BI-Berichten als Datumshierarchien verwendet werden können.
Welche drei Aktionen sollten Sie nacheinander ausführen? Um diese Frage zu beantworten, verschieben Sie die entsprechenden Aktionen aus der Aktionsliste in den Antwortbereich und ordnen Sie sie in der richtigen Reihenfolge an.

Reveal Solution  Discussion  0

Correct Answer:


Explanation:
Power Query should resolve this requirement before the data enters the semantic model. The chosen transformation preserves the required rows and grain while converting the source layout into an analysis- ready table. Use the selections preserved in the answer exhibit as the supported configuration. The technical decision turns on how to import attributes as columns from all the documents in the JSON file. A visual, measure, or model relationship cannot repair the incoming tabular shape; those features operate after the query result has already been loaded. This rationale is anchored to the PL-300 objective " Convert semi- structured data to a table " . This keeps the query output reproducible at refresh and leaves the semantic model with the grain and schema required by the report.
Microsoft Learn reference: https://learn.microsoft.com/en-us/power-query/best-practices | PL-300 objective: " Convert semi-structured data to a table " | Study guide: https://learn.microsoft.com/en-us/credentials
/certifications/resources/study-guides/pl-300

Question #3

Sie müssen die erforderliche Beziehung für die Visualisierung des Managers erstellen. Was müssen Sie tun, bevor Sie die Beziehung erstellen können?

  • A. Ändern Sie den Datentyp von sales[sales_id] in Text.
  • B. Ändern Sie den Datentyp von sales [region_id] in Dezimalzahl.
  • C. Ändern Sie den Datentyp von Sales[region_id] in Ganze Zahl.
  • D. Fügen Sie in der Tabelle "Sales" eine Kennzahl für sum(sales_amount) hinzu.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #4

Sie müssen eine Visualisierung erstellen, die Einnahmen und Kosten im Laufe der Zeit vergleicht.
Welche Art von Visualisierung sollten Sie verwenden?

  • A. Wasserfalldiagramm
  • B. Liniendiagramm
  • C. Ringdiagramm
  • D. gestapeltes Flächendiagramm
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Explanation: Only visible for Actual4test members. You can sign-up / login (it's free).

Question #5

Sie versuchen, Purer 81 Desktop mit einer Cassandra-Datenbank zu verbinden.
Aus der Liste der Datenkonnektoren geht hervor, dass es keinen spezifischen Konnektor für die Cassandra-Datenbank gibt. Sie müssen einen alternativen Datenkonnektor auswählen, der eine Verbindung zur Datenbank herstellt.
Welchen Stecker sollten Sie wählen?

  • A. ODBC
  • B. Microsoft SQL Server-Datenbank
  • C. OData
  • D. OLE DB
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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