The Importance Of Microsoft Power BI Data Analyst Certification Exam For A Career In IT
The world of IT is changing rapidly. The demand for skilled professionals has reached its peak. With the increase in number of software companies, the competition has also increased. There are a lot of opportunities for professionals with high level skills. One such skill is Microsoft Power BI Data Analyst Certification Exam. This exam is designed to test your knowledge on data analysis concepts and also on different tools that you can use to solve problems related to data analysis.
There are many ways to get certified as a data analyst or BI professional. You can go through a formal education program or attend classes offered by various institutions and organizations. However, if you want to ensure that you get the best job opportunities and get hired easily, then getting certified is what you need to do. Here at ExamBoosts our Microsoft PL-300 Dumps will help you to get certified. Basic measures of column chart scenario have scenario based questions that shared dataset of calculated table.
Exam PL-300: Microsoft Power BI Data Analyst
The Power BI data analyst delivers actionable insights by leveraging available data and applying domain expertise. The Power BI data analyst collaborates with key stakeholders across verticals to identify business requirements, cleans and transforms the data, and then designs and builds data models by using Power BI. The Power BI data analyst provides meaningful business value through easy-to-comprehend data visualizations, enables others to perform self-service analytics, and deploys and configures solutions for consumption. Candidates for this exam should be proficient using Power Query and writing expressions by using DAX.
Passing score: 700. Learn more about exam scores.
Part of the requirements for: Microsoft Certified: Power BI Data Analyst Associate
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Microsoft Power BI Data Analyst Exam Certification Details:
What is the salary of the Microsoft Power BI Data Analyst Certified professional
The Average salary of different countries of Microsoft Power BI Data Analyst certified professionals:
United States; USD 90,000
United Kingdom; POUNDS 60,000
India; INR 500,000
Canada; CAD 70,000
Australia; AUD 75,000
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/pl-300
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Microsoft PL-300日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Visualize and analyze data | 25-30% | - Enhance reports with analytics
- 1. Apply conditional formatting and custom visuals
- 2. Create paginated reports
- 3. Use AI visuals, forecasts, and key influencers
- Perform data analysis
- 1. Interpret results and identify trends
- 2. Create and manage bookmarks and tooltips
- 3. Implement custom visuals and R/Python scripts
- Create reports and dashboards
- 1. Choose appropriate visualizations
- 2. Create dashboards and pinned elements
- 3. Design report layout, formatting, and interactivity
- 4. Apply filters, slicers, and drill-through
|
| Topic 2: Prepare the data | 25-30% | - Profile and clean data
- 1. Manage data types, columns, and rows
- 2. Evaluate data statistics and column properties
- 3. Resolve inconsistencies, null values, and errors
- 4. Transform data using Power Query Editor
- Load and configure data
- 1. Integrate data from multiple sources
- 2. Define table structures and properties
- 3. Configure data refresh settings
- Get or connect to data
- 1. Create and modify parameters
- 2. Choose storage modes: Import, DirectQuery, DirectLake
- 3. Configure data source settings, credentials, and privacy levels
- 4. Identify and connect to data sources or shared semantic models
|
| Topic 3: Manage and secure Power BI | 15-20% | - Implement security and governance
- 1. Configure row-level security (RLS) and object-level security
- 2. Apply data sensitivity labels and protection
- 3. Manage permissions and access
- Manage workspaces and assets
- 1. Create and configure workspaces
- 2. Publish, update, and organize reports/datasets
- 3. Manage data refresh and scheduled updates
- Deploy and distribute content
- 1. Share reports, dashboards, and apps
- 2. Embed content in applications or websites
- 3. Monitor usage and performance
|
| Topic 4: Model the data | 25-30% | - Design data models
- 1. Create relationships: cardinality, cross-filter direction, security
- 2. Define tables, columns, and hierarchies
- 3. Create common date tables
- 4. Implement role-playing dimensions
- Optimize model performance
- 1. Optimize relationships and calculations
- 2. Reduce cardinality and data size
- 3. Use aggregations and composite models
- Create model calculations
- 1. Use CALCULATE and filter context
- 2. Use DAX: calculated columns, calculated tables, measures
- 3. Implement aggregation and time intelligence
|