Academy | Syllabus
Microsoft Certified: Power BI Data Analyst Associate
This program will demonstrate methods and best practices that align with business and technical requirements for modeling, visualizing, and analyzing data with Microsoft Power BI. Participants will learn how to provide meaningful business value through easy-to-comprehend data visualizations, enable others to perform self-service analytics, deploy and configure solutions for consumption.
Trusted by OrganizationsProven by Professionals
+21
Years of Experiences
+6.000
Delivered Training Programs
+50.000
Professionals
90%
Exam Pass Rate
Program Details
Durations
The program is a 5-day intensive training class.
Method of Delivery
The program provided by Multimatics will be delivered through interactive presentation by professional instructor(s), group debriefs, individual and team exercises, behavior modelling and roleplays, one-to-one and group discussion, case studies, and projects.
Who Should Attend?
The target audience for Microsoft Power BI is broad, encompassing both technical users (like data analysts, data scientists, developers, and IT administrators) who build solutions and business users (like managers and department heads) who need to interpret data and dashboards to make decisions.
Program Objectives
By the end of the program, participants will be able to:
- Prepare the data
- Model the data
- Visualize and analyze the data
- Manage and secure Power BI
Examination Details
Duration
5 Days
Format
- Open BookClose Book
Level
Intermediate
Passing Grade
65%
Program Modules
Prepare the Data
Topic Covered
- 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