This certification exam covers a range of skills that the applicants need to develop competency in before sitting for it. These skills are broken into topics and subtopics. Here are the highlights of the subject areas covered in Microsoft DA-100:

• Prepare Data: 20-25%

  This section of the certification exam will evaluate the ability of the candidates to acquire data from various data sources. They also must be able to profile data, which includes identifying data anomalies and examining data structure. It also requires interrogating data statistics and column properties. In addition, the test takers should have competence in cleaning, transforming, and loading the data. This involves resolving inconsistencies, identifying the relevant keys for joins, combining queries, and resolving data import errors.

• Maintain & Deploy Deliverables: 10-15%

  The applicants for the Microsoft DA-100 exam should also have competence in managing datasets. This involves configuring datasets scheduled refresh, certifying or promoting Power BI content, and providing access to the datasets. The learners also need to have the skills in creating and managing workspaces, creating and configuring workspaces, assigning workspace roles, and using deployment pipelines.

• Visualize Data: 20-25%

  Within this domain, the examinees should possess the ability to create reports because the certification test will measure their capability to perform the technical tasks in this area. They will also need to demonstrate their skills in creating dashboards, including setting mobile view, using Q&A features, managing tiles on dashboards, and configuring data classification. The individuals should also be able to improve reports for usability. They will be required to demonstrate their skills in configuring bookmarks, applying to sort, creating custom tooltips, exporting report data, and configuring Sync Slicers.

• Analyze Data: 10-15%

  This part will measure the competence of the students in improving reports to reveal insights. These include competence in applying conditional formatting, personalizing visuals, exploring statistical summary, and using Q&A visuals. It will also evaluate their skills in performing advanced analysis.

• Model Data: 25-30%

  This topic equips the candidates with the skills and knowledge on how to design the data model. The questions from this subject area will measure their expertise in defining tables, quick measures, role-playing dimensions, cross-filter direction and relationship’s cardinality, and precise level of data granularity. It will also measure competence in the development of data models, creation of measures with the use of DAX, and optimization of model performance.

Microsoft DA-100 Practice Test Questions, Microsoft DA-100 Exam Practice Test Questions

The candidates who want to earn the Microsoft Certified: Data Analyst Associate certification must pass one qualifying exam, which is Microsoft DA-100. This test evaluates the ability of the test takers to accomplish specific technical tasks. These include the processes with data, such as analyzing, preparing, maintaining and deploying, visualizing, and modeling.

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

Understanding functional and technical aspects of Exam DA-100: Analyzing Data with Microsoft Power BI Model the data

The following will be discussed in MICROSOFT DA-100 exam dumps:

• Define the tables
• Use CALCULATE to manipulate filters
• Replace numeric columns with measures
• Create hierarchies
• Remove unnecessary rows and columns
• Create calculated columns
• Identify poorly performing measures, relationships, and visuals
• Develop a data model
• Define role-playing dimensions
• Create a common date table
• Design a data model
• Create calculated tables
• Implement Time Intelligence using DAX
• Flatten out a parent-child hierarchy
• Define the appropriate level of data granularity
• Use basic statistical functions to enhance data
• Resolve many-to-many relationships
• Improve cardinality levels by changing data types
• Create semi-additive measures
• Design the data model to meet performance requirements
• Implement row-level security roles
• Define a relationship's cardinality and cross-filter direction
• Create measures by using DAX
• Set up the Q&A feature
• Define quick measures
• Use DAX to build complex measures
• Configure table and column properties
• Improve cardinality levels through summarization
• Optimize model performance
• Apply cross-filter direction and security filtering
• Create and manage aggregations