PL-300: Microsoft Power BI Data Analyst

This course provides a comprehensive introduction to Microsoft 365, Copilot, and AI-powered agents. Introduces the core concepts, core services, and admin controls of Microsoft 365. From this foundation, it delves into how Copilot and agents can use AI to automate tasks, improve collaboration, and personalize the user experience across the Microsoft 365 ecosystem.

This official course corresponds to the content designed by Microsoft with the name AB-900T00: Introduction to Microsoft 365 and AI Administration.

About this course

Microsoft Power Platform helps organizations optimize their operations by simplifying, automating and transforming business tasks and processes. In this course, students will discuss the various methods and best practices that are aligned with the commercial and technical requirements for modeling, visualizing and analyzing data with Power BI. This training will also show you how to access and process data from a variety of data sources, including relational and non-relational data.

In addition, it will also teach how to implement proper security standards and policies across the Power BI spectrum, including data sets and groups. The course will also discuss how to manage and deploy reports and dashboards to share and distribute content.

Who is it aimed at?

This learning path introduces the Microsoft 365 experience by helping you set up core services, manage users and access securely, and protect your organization’s data using built-in tools and best practices.

Objectives

Once the course is over, the student will have acquired the following knowledge and skills:
Ingest, clean and transform data
Modeling data for performance and scalability
Design and create reports for data analysis
Apply and perform advanced report analysis
Manage and share report assets

Program

Module 3: Create interactive reports with Copilot for Power BI.
Prepare your data to use with Copilot for Power BI.
Use Copilot for Power BI to model data.
Create reports with Copilot for Power BI.
Create summaries with Copilot for Power BI.

Module 4: Obtain data in Power BI.
Obtaining data from relational data sources.
Creation of dynamic reports with parameters.
Obtaining data from a NoSQL database.
Obtaining data from online services.
Select a storage mode.
Get data from Azure Analysis Services.
Fix performance problems.
Resolve data import errors.
Exercise: Data preparation in Power BI Desktop.

Module 5: Clean, transform and load data in Power BI.
Form of the initial data.
Simplification of the data structure.
Evaluation and change of column data types.
Combination of several tables into one.
Data profile generation in Power BI.
Using the advanced Editor to modify the code.
Exercise: Loading data in Power BI Desktop.

Module 6: Choosing a Power BI model framework.
Describe the basics of the Power BI model.
Determination of when to develop an import model.
Determine when to develop a DirectQuery model.
Determination of when to develop a composite model.
Choice of a model frame.

Module 8: Design a semantic model in Power BI.
Use of tables.
Create a date table.
Use of dimensions.
Definition of the granularity of the data.
Work with relationships and cardinality.
Solving modeling challenges.
Exercise: Data modeling in Power BI Desktop.

Module 10: Add measurements to Power BI Desktop models.
Creation of simple measures.
Creation of compound measures.
Creation of rapid measures.
Comparison of the calculated columns with the measurements.
Knowledge check.
Exercise: Creating DAX calculations in Power BI Desktop.

Module 12: Optimization of a model for performance in Power BI.
Introduction to performance optimization.
Review of the performance of measures, relationships and visual objects.
Use of variables to improve performance and solve problems.
Reduction of cardinality.
Optimization of DirectQuery models with table-level storage.
Creation and management of aggregations.

Module 13: Definition of the scope of the report design requirements.
Identification of the public.
Determination of the types of report.
Definition of the graphical user interface requirements.
Definition of user experience requirements.
Exploration of report designs.

Module 14: Design Power BI reports.
Specification of the analytical report design.
Design of visually attractive reports.
Report objects.
Selection of visuals from report.
Selection of report visuals adapted to the report design.
Format and configuration of visualizations.
Use of key performance indicators.
Exercise: Designing a report in Power BI Desktop.

Module 16: Configure report filters in Power BI.
Introduction to report design for filtering.
Application of filters to the report structure.
Application of filters with segmentations.
Design of reports with advanced filtering techniques.
Filtered in time of consumption.
Selection of report filter techniques.
Case study: Setting up feedback-based report filters.

Module 17: Improve report designs in Power BI for the user experience.
Design of reports to show details.
Design of reports to highlight values.
Design of reports that behave like applications.
I work with markers.
Design of reports for navigation.
I work with headers of visual objects.
Design of reports with integrated assistance.
Optimization of reporting performance.
Optimization of reports for use on mobile devices.
Exercise: Improve Power BI reports.

Module 18: Perform analysis in Power BI.
Introduction to analysis.
Exploration of the statistical summary.
Identification of atypical values with Power BI visuals.
Grouping and discretization of data for analysis.
Application of cluster clustering techniques.
Performing time series analysis.
Use of the Analyze feature.
Creation of hypothesis parameters.
Use of specialized visual objects.
Exercise: Performing an advanced analysis with artificial intelligence visual objects.

Module 19: Create and manage workspaces in Power BI.
Distribution of a report or panel.
Monitoring of use and performance.
Recommendation of a development life cycle strategy.
Data troubleshooting by viewing their lineage.
Data protection configuration.

Module 20: Managing semantic models in Power BI.
Using a Power BI gateway to connect to local data sources.
Configuration of a scheduled semantic model update.
Configuration of incremental update options.
Troubleshoot service connectivity issues.
Increased performance with query caching (Premium).

Module 21: Create panels in Power BI.
Data alert configuration.
Data exploration by asking questions.
Review of Quick Conclusions.
Incorporation of a panel theme.
Anching an active report page to a dashboard.
Configuration of a real-time dashboard.
Establishment of the view for mobile devices.
Exercise: Creating a Power BI panel.

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Registration fee: €99

About this course

Who is it aimed at?

Objectives

Program

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