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Career Opportunities

The professionals with the Microsoft Certified: Data Analyst Associate certification are qualified for a variety of job titles. These include a Junior Data Analyst, an Associate Analyst, an Associate Consultant, a Certified Retail Analyst, a Technology Support Analyst, a Digital Media Analyst, and a Network Analyst. The average salary for these positions is $52,000 per annum.

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

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Microsoft DA-100 Exam Syllabus Topics:

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

Microsoft Analyzing Data with Microsoft Power BI : DA-100

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