What are the steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam
The steps to follow for the registration of the Microsoft Power BI Data Analyst Certification Exam are as follows:
The next step is to fill out your personal information such as name, email address, country and state city etc., which is mandatory to complete your registration process successfully.
You will see a list of courses that are available on this website. Select “Microsoft Power BI Data Analyst Certification Exam” and click on “Enroll Now” button.
Then you need to select your preferred payment method which includes credit card or PayPal account etc., and you will receive an email confirmation after successful payment using your credit card or PayPal account etc.
Go to the official website of Microsoft, and click on “Microsoft Learning”.
After successful registration process, you will receive an email confirmation from Microsoft with all the details about your course including access code etc., which will be sent to your registered email ID provided during registration process.
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Introduction of Microsoft PL-300 Exam
Microsoft offers a wide range of certifications to enhance your knowledge in various areas of IT. The Microsoft Power BI Data Analyst Certification Exam is one of the most popular and sought-after Microsoft certification exams which aims to develop your skills as a data analyst by providing you with an opportunity to learn about basic business intelligence concepts, data analysis techniques and tools that can be used for building data models. Microsoft PL-300 Dumps are the best way to pass your exam.
The Microsoft certification exams enable you to validate your knowledge and skills in the system. If you have a job, it helps you to get promoted. The certification is a must-have for IT professionals. Microsoft Power BI Data Analyst Certification Exam is an exam designed by Microsoft for data analysts who are interested in gaining knowledge of the Microsoft Azure cloud platform and Power BI suite tools. The exam tests your ability to design, develop, and implement analytical solutions using Excel, Power Pivot, Power View and other related tools.
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Microsoft PL-300 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Prepare the Data (15-20%) | |
| Get data from different data sources | - identify and connect to a data source - change data source settings - select a shared dataset or create a local dataset - select a storage mode - use Microsoft Dataverse - change the value in a parameter - connect to a data flow |
| Clean, transform, and load the data | - profile the data - resolve inconsistencies, unexpected or null values, and data quality issues - identify and create appropriate keys for joins - evaluate and transform column data types - shape and transform tables - combine queries - apply user-friendly naming conventions to columns and queries - configure data loading - resolve data import errors |
Model the Data (30-35%) | |
| Design a data model | - define the tables - configure table and column properties - design and implement role-playing dimensions - define a relationship's cardinality and cross-filter direction - design a data model that uses a star schema - create a common date table |
| Develop a data model | - create calculated tables - create hierarchies - create calculated columns - implement row-level security roles - use the Q&A feature |
| Create model calculations by using DAX | - create basic measures by using DAX - use CALCULATE to manipulate filters - implement Time Intelligence using DAX - replace implicit measures with explicit measures - use basic statistical functions - create semi-additive measures - use quick measures |
| Optimize model performance | - remove unnecessary rows and columns - identify poorly performing measures, relationships, and visuals - reduce cardinality levels to improve performance |
Visualize and Analyze the Data (25-30%) | |
| Create reports | - add visualization items to reports - choose an appropriate visualization type - format and configure visualizations - use a custom visual - apply and customize a theme - configure conditional formatting - apply slicing and filtering - configure the report page - use the Analyze in Excel feature - choose when to use a paginated report |
| Create dashboards | - manage tiles on a dashboard - configure mobile view - use the Q&A feature - add a Quick Insights result to a dashboard - apply a dashboard theme - pin a live report page to a dashboard |
| Enhance reports for usability and storytelling | - configure bookmarks - create custom tooltips - edit and configure interactions between visuals - configure navigation for a report - apply sorting - configure Sync Slicers - group and layer visuals by using the selection pane - drilldown into data using interactive visuals - export report data - design reports for mobile devices |
| Identify patterns and trends | - use the Analyze feature in Power BI - identify outliers - choose between continuous and categorical axes - use groupings, binnings, and clustering - use AI visuals - use the Forecast feature - create reference lines by using the Analytics pane |
Deploy and Maintain Assets (20-25%) | |
| Manage files and datasets | - identify when a gateway is required - configure a dataset scheduled refresh - configure row-level security group membership - provide access to datasets - manage global options for files |
| Manage workspaces | - create and configure a workspace - assign workspace roles - configure and update a workspace app - publish, import, or update assets in a workspace - apply sensitivity labels to workspace content - configure subscriptions and data alerts - promote or certify Power BI content |
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
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Microsoft PL-300 Deutsch Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Prepare the data | 15-20% | - Clean, transform, and load data
|
| Model the data | 30-40% | - Develop a data model
|
| Visualize and analyze data | 25-35% | - Enhance reports for usability
|
| Deploy and maintain assets | 15-20% | - Manage workspaces and datasets
|


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