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The topics covered in the Microsoft DA-100 exam include understanding the Power BI service and Power BI desktop interfaces, working with data sources, transforming and cleaning data, creating data models, designing and publishing reports, and sharing and collaborating on data. DA-100 exam consists of 40-60 multiple-choice questions, and candidates are given 2 hours to complete it.

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

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Microsoft DA-100 (Analyzing Data with Microsoft Power BI) Certification Exam is a valuable certification for data analysts and business professionals who work with data. It tests the skills and knowledge required to analyze and visualize data using Microsoft Power BI, and passing the exam can lead to career advancement opportunities and higher salaries. With the right preparation and study materials, candidates can successfully pass the exam and demonstrate their proficiency in data analysis with Power BI.

Microsoft DA-100 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Visualize the data	25%	- Create reports 1. Choose an appropriate visualization type 2. Configure conditional formatting 3. Import a custom visual 4. Add visualization items to reports 5. Create and manage bookmarks 6. Apply slicing and filtering 7. Format and configure visualizations - Create dashboards 1. Set mobile view 2. Manage tiles on a dashboard 3. Configure data alerts 4. Use the Q&A feature - Enforce accessibility 1. Configure tab order 2. Design accessible reports 3. Use accessibility features
Topic 2: Prepare the data	20%	- Transform and load the data 1. Create and transform columns 2. Design a star schema 3. Create and transform tables 4. Select appropriate column data types 5. Define relationship cardinality and cross-filter direction - Get data from different data sources 1. Identify and connect to a data source 2. Select a storage mode 3. Select a shared dataset or create a local dataset 4. Change data source settings 5. Choose an appropriate Power BI data source - Profile the data 1. Identify data anomalies 2. Interpret data distribution and variance 3. Examine data structures - Clean the data 1. Resolve data import errors 2. Resolve inconsistencies, unexpected or null values, and data quality issues 3. Evaluate data, including data statistics and column properties
Topic 3: Deploy and maintain deliverables	10%	- Manage datasets 1. Configure row-level security group membership 2. Configure a dataset scheduled refresh 3. Provide access to datasets 4. Configure cross-workspace sharing - Create and manage workspaces 1. Assign workspace roles 2. Create and configure a workspace 3. Configure and update a workspace app
Topic 4: Model the data	30%	- Design a data model 1. Configure table and column properties 2. Define quick measures 3. Define the tables 4. Define a relationship's cross-filter direction and security filtering 5. Design and implement role-playing dimensions - Develop a data model 1. Create calculated columns 2. Create hierarchies 3. Create calculated tables 4. Implement row-level security roles - Create measures by using DAX 1. Use DAX aggregation functions 2. Create semi-additive measures 3. Implement Time Intelligence using DAX 4. Use DAX logical functions 5. Create calculated measures - Optimize model performance 1. Optimize Power Query transformations 2. Improve performance by identifying and removing unnecessary rows and columns 3. Improve performance by choosing optimal data types
Topic 5: Analyze the data	15%	- Perform advanced analysis 1. Identify outliers 2. Use advanced analytical custom visuals 3. Perform What-if analysis 4. Use the Analyze feature - Enhance reports for usability and storytelling 1. Configure sync slicers 2. Create custom tooltips 3. Edit and configure interactions between visuals 4. Group and layer visuals 5. Configure bookmarks 6. Configure navigation for a report 7. Apply sorting