We provide online course about PL-300 Design and manage analytics solutions using Power BI in english. This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI.
Content:
The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.
Agenda:
Module 1 - Get started with Microsoft data analytics:
• Discover data analysis
• Get started building with Power BI
• Introduction to end-to-end analytics using Microsoft Fabric
Module 2 - Prepare data for analysis with Power BI:
• Get data in Power BI
• Clean, transform, and load data in Power BI
• Choose a Power BI model framework
Module 3 - Model data with Power BI:
• Configure a semantic model
• Write DAX formulas for semantic models
• Create DAX calculations in semantic models
• Use DAX time intelligence functions in semantic models
• Create visual calculations in Power BI Desktop
• Optimize a model for performance in Power BI
Module 4 - Design effective reports in Power BI:
• Scope report design requirements
• Design Power BI reports
• Enhance Power BI report designs for the user experience
• Perform analytics in Power BI
Module 5 - Manage and secure Power BI:
• Manage workspaces in Power BI service
• Manage semantic models in Power BI
• Choose a content distribution method
• Create dashboards in Power BI
• Secure data access in Power BI
Target audience:
The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.
Prerequisites:
• Understanding of core data concepts
• Knowledge of working with relational and non-relational data
• Knowledge of data analysis and visualization concepts
Language:
• This course is given in english