Name: الشهاده المعتمدة محلل Power BI
Author: Taha Hussien

Pl 300: Power BI analyst
صادرة من Microsoft
تؤكد شهادة Microsoft Pl 300: Power BI Analyst القدرة على تصميم وتطوير ونشر حلول ذكاء الأعمال (BI) باستخدام Power BI ، وهي أداة لتصور البيانات وتحليلها. وهي مصممة للأفراد الذين يرغبون في تعلم كيفية استخدام Power BI لإنشاء لوحات تحكم وتقارير وحلول BI أخرى.

Audience profile

As a candidate for this exam, you should deliver actionable insights by working with available data and applying domain expertise. You should:

Provide meaningful business value through easy-to-comprehend data visualizations.
Enable others to perform self-service analytics.

As a Power BI data analyst, you work closely with business stakeholders to identify business requirements. You collaborate with analytics engineers and data engineers to identify and acquire data. You use Power BI to:

Prepare the data
Model the data
Visualize and analyze data
Manage and secure Power BI

You should be proficient at using Power Query and Data Analysis Expressions (DAX).

Skills at a glance

Prepare the data (25–30%)
Model the data (25–30%)
Visualize and analyze the data (25–30%)
Manage and secure Power BI (15–20%)

Prepare the data (25–30%)

Get or connect to data

Identify and connect to data sources or a shared semantic model
Change data source settings, including credentials and privacy levels
Choose between DirectQuery and Import
Create and modify parameters

Profile and clean the data

Evaluate data, including data statistics and column properties
Resolve inconsistencies, unexpected or null values, and data quality issues
Resolve data import errors

Transform and load the data

Select appropriate column data types
Create and transform columns
Group and aggregate rows
Pivot, unpivot, and transpose data
Convert semi-structured data to a table
Create fact tables and dimension tables
Identify when to use reference or duplicate queries and the resulting impact
Merge and append queries
Identify and create appropriate keys for relationships
Configure data loading for queries

Model the data (25–30%)

Design and implement a data model

Configure table and column properties
Implement role-playing dimensions
Define a relationship’s cardinality and cross-filter direction
Create a common date table
Identify use cases for calculated columns and calculated tables

Create model calculations by using DAX

Create single aggregation measures
Use the CALCULATE function
Implement time intelligence measures
Use basic statistical functions
Create semi-additive measures
Create a measure by using quick measures
Create calculated tables or columns
Create calculation groups

Optimize model performance

Improve performance by identifying and removing unnecessary rows and columns
Identify poorly performing measures, relationships, and visuals by using Performance Analyzer and DAX query view
Improve performance by reducing granularity