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What should you know about the Microsoft DA-100 exam before going for it?

The intended candidates for the Microsoft DA-100 exam are Data Analysts. These professionals help the organizations make the most of the value of data assets through the use of Microsoft Power BI. They also collaborate with the major stakeholders across the company to deliver the appropriate insights based on the recognized business prerequisites.

Microsoft DA-100 is an associate-level certification test, and as such, it does not have any official prerequisites. However, Microsoft recommends that the students have a good fundamental knowledge of data processing and data repositories both in Cloud and on-premises. The candidates for the exam should have the relevant skills in building and designing scalable data models, facilitating advanced analytic abilities, and transforming and cleaning data to provide significant business value through understandable data visualizations.

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How can you prepare for the Microsoft DA-100 exam to succeed?

The candidates can explore various resources to prepare for the Microsoft DA-100 exam. The Microsoft Learning Platform offers many study tools that the learners can use to achieve success in their test. The first step in the preparation process is to go over the detailed exam topics. After that, you can choose your resources carefully. Here are the official recommended materials for the DA-100 test:

Instructor-Led Training
Microsoft recommends the Analyzing Data with Power BI training course for the candidates taking the DA-100 test. This training focuses on different best practices and methods associated with the technical and business requirements for visualizing, analyzing, and modeling data with Power BI. The individuals will learn how to process and access data from different data sources, including non-relational and relational data.
Practice Test
Microsoft also offers the official practice test for Microsoft DA-100. The exam questions cover all the objectives of the actual test. This means that you will be well prepared for any questions that may be administered in the exam.
Books
The recommended book resource for this test is Exam Ref: DA-100 Analyzing Data with Microsoft Power BI by Daniil Maslyuk. This is a professional-level resource to help the learners optimize their performance in the test and improve their skills. The book can be found on the Microsoft Press Store.
Free Online Training
The applicants who prefer self-paced study can explore the learning paths for the Microsoft DA-100 exam. There are six learning paths for this certification test, including Getting Started with Microsoft Data Analytics, Prepare Data for Analysis, Model Data in Power BI, and Visualize Data in Power BI, among others. Each path contains different modules that address particular topics of the exam.

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

Microsoft DA-100 Exam Syllabus Topics:

Section	Weight	Objectives
Visualize the data	25-30%	- Create reports 1. Use visuals such as charts, maps, and tables 2. Design interactive reports in Power BI Desktop - Enhance reports 1. Use bookmarks and navigation elements 2. Apply filters, slicers, and drill-through
Model the data	25-30%	- Create calculated columns and measures 1. Use DAX for calculations 2. Optimize model performance - Design data models 1. Design star and snowflake schemas 2. Create relationships between tables
Analyze the data	10-15%	- Perform advanced analytics 1. Apply statistical measures in reports 2. Use DAX time intelligence functions - Analyze data patterns 1. Use AI visuals and quick insights 2. Identify trends and outliers
Deploy and maintain deliverables	10-15%	- Secure and share content 1. Implement row-level security (RLS) 2. Share dashboards with users and groups - Manage workspaces and datasets 1. Publish reports to Power BI Service 2. Configure dataset refresh schedules
Prepare the data	20-25%	- Clean and transform data 1. Handle missing, duplicate, and inconsistent data 2. Use Power Query Editor for data shaping - Get data from data sources 1. Connect to data sources (files, databases, cloud services) 2. Select appropriate storage modes (Import, DirectQuery, Composite)