Microsoft DA-100 Deutsch dumps - in .pdf

DA-100 Deutsch pdf
  • Exam Code: DA-100 Deutsch
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)
  • Updated: Aug 15, 2026
  • Q & A: 150 Questions and Answers
  • PDF Price: $69.99
  • Free Demo

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  • Exam Code: DA-100 Deutsch
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)
  • Updated: Aug 15, 2026
  • Q & A: 150 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Microsoft DA-100 Deutsch dumps - Testing Engine

DA-100 Deutsch Testing Engine
  • Exam Code: DA-100 Deutsch
  • Exam Name: Analyzing Data with Microsoft Power BI (DA-100 Deutsch Version)
  • Updated: Aug 15, 2026
  • Q & A: 150 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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Ideal Audience and Required Skills

DA-100 is intended for data analysts who use MS Power BI to enhance the value of the data their organization holds. These professionals are responsible for polishing and transforming data, creating expandable data models, and performing data visualizations that can be interpreted and analyzed to withdraw critical information. Data analysts also work alongside other stakeholders of the business to provide relevant data according to their company’s requirements. Thus, a strong prior understanding of both cloud & on-premises data processing and data repositories is also required by those specialists who are going to take test DA-100.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/da-100

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Compared to other visualization tools we would recommend that Power BI is quite user friendly and is relatively easy to learn. What also contributes to this is that the Power BI desktop version is available for free, resulting in a pretty large user base on the internet, which is beneficial to your learning curve, as in our experience answers to particular questions can be found easily most of the times.

Microsoft DA-100 Deutsch Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Model the data30%- Develop a data model
  • 1. Create calculated columns
  • 2. Create hierarchies
  • 3. Create calculated tables
  • 4. Implement row-level security roles
- Design a data model
  • 1. Define quick measures
  • 2. Design and implement role-playing dimensions
  • 3. Define the tables
  • 4. Configure table and column properties
  • 5. Define a relationship's cross-filter direction and security filtering
- Optimize model performance
  • 1. Optimize Power Query transformations
  • 2. Improve performance by choosing optimal data types
  • 3. Improve performance by identifying and removing unnecessary rows and columns
- Create measures by using DAX
  • 1. Use DAX logical functions
  • 2. Implement Time Intelligence using DAX
  • 3. Create calculated measures
  • 4. Create semi-additive measures
  • 5. Use DAX aggregation functions
Topic 2: Visualize the data25%- Create reports
  • 1. Add visualization items to reports
  • 2. Configure conditional formatting
  • 3. Create and manage bookmarks
  • 4. Import a custom visual
  • 5. Apply slicing and filtering
  • 6. Format and configure visualizations
  • 7. Choose an appropriate visualization type
- Enforce accessibility
  • 1. Configure tab order
  • 2. Use accessibility features
  • 3. Design accessible reports
- Create dashboards
  • 1. Set mobile view
  • 2. Use the Q&A feature
  • 3. Configure data alerts
  • 4. Manage tiles on a dashboard
Topic 3: Analyze the data15%- Enhance reports for usability and storytelling
  • 1. Group and layer visuals
  • 2. Configure sync slicers
  • 3. Configure bookmarks
  • 4. Configure navigation for a report
  • 5. Edit and configure interactions between visuals
  • 6. Apply sorting
  • 7. Create custom tooltips
- Perform advanced analysis
  • 1. Use the Analyze feature
  • 2. Identify outliers
  • 3. Use advanced analytical custom visuals
  • 4. Perform What-if analysis
Topic 4: Prepare the data20%- Clean the data
  • 1. Resolve data import errors
  • 2. Evaluate data, including data statistics and column properties
  • 3. Resolve inconsistencies, unexpected or null values, and data quality issues
- Profile the data
  • 1. Examine data structures
  • 2. Identify data anomalies
  • 3. Interpret data distribution and variance
- Get data from different data sources
  • 1. Change data source settings
  • 2. Identify and connect to a data source
  • 3. Select a storage mode
  • 4. Choose an appropriate Power BI data source
  • 5. Select a shared dataset or create a local dataset
- Transform and load the data
  • 1. Create and transform columns
  • 2. Define relationship cardinality and cross-filter direction
  • 3. Create and transform tables
  • 4. Design a star schema
  • 5. Select appropriate column data types
Topic 5: Deploy and maintain deliverables10%- Create and manage workspaces
  • 1. Assign workspace roles
  • 2. Create and configure a workspace
  • 3. Configure and update a workspace app
- Manage datasets
  • 1. Provide access to datasets
  • 2. Configure cross-workspace sharing
  • 3. Configure row-level security group membership
  • 4. Configure a dataset scheduled refresh

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