Course Description: PL-300: Microsoft Power BI Data Analyst

This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a variety of data sources, including relational and non-relational data. This course will also explore how to implement appropriate security standards and policies across the entire spectrum of Power BI, including data sets and groups. The course will also discuss how to manage and implement reports and dashboards for sharing and distributing content.

Public Profile

The audience for this course is data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also intended for those who develop reports that visualize data from data platform technologies that exist both in the cloud and on-premises.

Items in this collection

• Description of data analysis (6 Units)
• Introduction to building with Power BI (6 Units)
• Obtaining data in Power BI (12 Units)
• Cleaning, transforming and loading data in Power BI (10 Units)
• Design of a data model in Power BI (10 Units)
• Introduction to creating measures with DAX in Power BI (10 units)
• Optimize a model for performance in Power BI (8 Units)
• Using Power BI visuals (10 units)
• Creating a data-driven story with Power BI reports (15 Units)
• Creating dashboards in Power BI (11 Units)
• Performing analysis in Power BI (12 Units)
• Working with artificial intelligence visuals in Power BI (7 Units)
• Creation and management of work areas in Power BI (8 Units)
• Managing Data Sets in Power BI (11 Units)
• Implementation of row level security (5 Units)

Course outline

Module 1: Introduction to Microsoft Data Analytics

This module explores the different roles in the data space, describes the important roles and responsibilities of a data analyst, and then explores the Power BI portfolio landscape.

Lessons

• Data analytics and Microsoft

• Introduction to Power BI

After completing this module, students will be able to:

• Explore different roles in data

• Identify the tasks performed by a data analyst

• Describe the Power BI product and service landscape

• Use the Power BI service

Module 2: Getting data in Power BI

This module explores the identification and recovery of data from various data sources. You'll also learn data connectivity and storage options, and understand the difference and performance implications of connecting directly to data versus importing it.

Lessons

• Data analytics and Microsoft

• Optimize performance

• Data error resolution

Lab: Data Preparation in Power BI Desktop

• Data preparation

After completing this module, students will be able to:

• Identify and retrieve data from different data sources

• Understand connection methods and their performance implications

• Use Microsoft Dataverse

• Connect to a data stream

Module 3: Cleaning, transforming and loading data in Power BI

This module teaches you the profiling process and understanding the state of the data. They will learn how to identify anomalies, observe the size and shape of their data, and perform appropriate data cleaning and transformation steps to prepare the data for loading into the model.

Lessons

• Data modeling

• Data Profiling

• Improve data structure

Lab: Loading data into Power BI Desktop

• Load data

After completing this module, students will be able to:

• Apply data shape transformations

• Improve data structure

• Profile and examine data

Module 4: Designing a data model in Power BI

This module teaches the fundamental concepts of designing and developing a data model for proper performance and scalability. This module will also help you understand and address many of the common data modeling issues, including relationships, security, and performance.

Lessons

• Introduction to data modeling

• Work with tables

• Dimensions and hierarchies

Lab: Data Modeling in Power BI Desktop

• Create model relationships

• Setting properties of tables and columns

• Create hierarchies

After completing this module, students will be able to:

• Understand the basics of data modeling

• Define relationships and their cardinality

• Implement dimensions and hierarchies

Module 5: Creating model calculations with DAX in Power BI

This module introduces you to the world of DAX and its true power to improve a model. You will learn about aggregations and the concepts of measures, calculated columns and tables, and time intelligence functions to solve calculation and data analysis problems.

Lessons

• Introduction to DAX

• Real-time dashboards

• Advanced DAX

Lab: Introduction to DAX in Power BI Desktop

• Create calculated tables

• Create calculated columns

• Create measures

Lab: Advanced DAX in Power BI Desktop

• Use the CALCULATE() function to manipulate the filter context

• Use time intelligence functions

After completing this module, students will be able to:

• Understanding DAX

• Use DAX for simple formulas and expressions

• Create tables and calculated measures

• Build simple measurements

• Work with time intelligence and key performance indicators

Module 6: Optimizing Model Performance in Power BI

In this module, you are introduced to the data modeling steps, processes, concepts, and best practices needed to optimize a data model for enterprise-level performance.

Lessons

• Optimizing the data model for performance

• Optimize DirectQuery models

After completing this module, students will be able to:

• Understand the importance of variables

• Improve the data model

• Optimize the storage model

Module 7: Creating reports in Power BI

This module introduces you to the fundamental concepts and principles of designing and creating a report, including selecting the right visual elements, designing the page layout, and applying basic but critical functions. The important topic of design for accessibility is also covered.

Lessons

• Design a report

• Improve the report

Lab: Improving reports with interaction and formatting in Power BI Desktop

• Create and configure slicer sync

• Create a drillthrough page

• Apply conditional formatting

• Create and use bookmarks

Lab: Designing a report in Power BI Desktop

• Design a report

• Configure visual fields and format properties

After completing this module, students will be able to:

• Map out a report page layout

• Select and add effective visualizations

• Add basic reporting functionality

• Add navigation and report interactions

Module 8: Creating dashboards in Power BI

In this module, you will learn how to tell a compelling story by using panels and the different navigation tools available to provide navigation. You will be introduced to features and functionality and how to improve dashboards for usability and insights.

Lessons

• Creating a dashboard

• Real-time dashboards

• Improve a panel

Lab: Create a dashboard in the Power BI service

• Creating a dashboard

• Pin visuals to a dashboard

• Use Q&A to create a dashboard tile

After completing this module, students will be able to:

• Creating a dashboard

• Understand dashboards in real time

• Improve the usability of a dashboard

Module 9: Identifying Power BI Patterns and Trends

This module helps you apply additional features to enhance the report to gain analytical insights into your data, providing you with the necessary steps to use the report for real data analysis. It will also perform advanced analysis using AI images in the report to get even deeper and more meaningful data insights.

Lessons

• Advanced analysis

• Insights into data through AI visuals

Lab: Data Analysis in Power BI Desktop

• Create animated scatter plots

• Use the visual to forecast values

After completing this module, students will be able to:

• Using the Analyze Feature

• Identify outliers in data

• Use AI visuals

• Use the advanced analytics custom visual

Module 10: Creating and managing workspaces in Power BI

This module will introduce you to workspaces, including how to create and manage them. You'll also learn how to share content, including reports and dashboards, and then learn how to distribute an application.

Lessons

• Create work areas

• Share and manage resources

After completing this module, students will be able to:

• Creating and managing a workspace

• Understand collaboration in the workplace

• Monitor work area usage and performance

• Distribute an application

Module 11: Managing Files and Datasets in Power BI

In this module you will see the parameters and data sets. You will also learn how to manage data sets and parameters, create dynamic reports with parameters, and set data set refresh options.

Lessons

• Parameters

• Data sets

After completing this module, students will be able to:

• Data Set and Parameter Management

• Creating dynamic reports with parameters

• Scheduling Data Set Updates

• Troubleshooting Gateway Service Connectivity

Module 12: Row Level Security in Power BI

In this module you will see row level security, static and dynamic methods and how to implement them.

Lessons

• Security in Power BI

Lab: Applying Row Level Security

• Set up many-to-many relationships

• Apply row level security

After completing this module, students will be able to:

• Implementing row-level security using Static and Dynamic methods

Previous requirements

Eligible data analysts enter this role with experience working with data in the cloud.

Specifically:

• Understanding of basic data concepts.
• Knowledge of how to work with relational data in the cloud.
• Knowledge of how to work with non-relational data in the cloud.
• Knowledge of data visualization and analysis concepts.

You can meet the prerequisites and better understand how to work with data in Azure by completing the Microsoft Azure Data Fundamentals before taking this course.

Language

• Course: English / Spanish

• Labs: English