Microsoft Power BI Data Analyst: PL-300T00 Course

Four days • Instructor-led training • Virtual course

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Course summary: Analysing Data with Power BI

The Microsoft Power BI Data Analyst training course teaches the methods of modeling, visualising, and analysing data with Power BI. This Microsoft PL-300T00 (previously DA-100) course covers the following topics:

  • accessing and processing data from a range of data sources (relational and non-relational)
  • implementing security standards and policies across datasets and groups
  • management and deployment of reports and dashboards for sharing and content distribution
  • build paginated reports and publishing them to a workspace for inclusion within Power BI

Training details

  • Format: instructor-led, virtual
  • Length: 4 days
  • Price: £1990 (+VAT)

Certification

This Power BI training course prepares you for exam PL-300: Microsoft Power BI Data Analyst. Those who succeed in the exam will gain Microsoft Certified: Power BI Data Analyst Associate status.

Microsoft Certified Data Analyst Associate badge for DA-100 course

Skills gained

By the end of this PL-300 training, you will be able to:

  • ingest, clean, and transform data
  • model data for performance and scalability
  • design and create reports for data analysis
  • apply and perform advanced report analytics
  • manage and share report assets
  • create paginated reports in Power BI

Analysing Data with Power BI

PL-300 Course

  • Instructor-led virtual training
  • 4 days
  • £1990 (+VAT)

Register


Audience profile

Learning goals

This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analysing data with Power BI. 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.

Applicable job roles

Power BI data analyst.

Prerequisites

Students on the PL-300 course should have prior cloud experience, including:

  • an understanding of core data concepts
  • knowledge of working with relational data in the cloud
  • knowledge of working with non-relational data in the cloud
  • knowledge of data analysis and visualisation concepts

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    Course outline

    Module 1: Get Started with Microsoft Data Analytics

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

    Lessons

    • Data Analytics and Microsoft
    • Getting Started with Power BI

    Lab: Getting Started

    • Getting Started

    After completing this module, students will be able to:

    • Explore the different roles in data
    • Identify the tasks that are performed by a data analyst
    • Describe the Power BI landscape of products and services
    • Use the Power BI service

    Module 2: Prepare Data in Power BI

    This module explores identifying and retrieving data from various data sources. You will also learn the options for connectivity and data storage, and understand the difference and performance implications of connecting directly to data vs. importing it.

    Lessons

    • Get data from various data sources
    • Optimise performance
    • Resolve data errors

    Lab: Preparing Data in Power BI Desktop

    • Prepare Data

    After completing this module, students will be able to:

    • Identify and retrieve data from different data sources
    • Understand the connection methods and their performance implications
    • Optimise query performance
    • Resolve data import errors

    Module 3: Clean, Transform, and Load Data in Power BI

    This module teaches you the process of profiling and understanding the condition of the data. They will learn how to identify anomalies, look at the size and shape of their data, and perform the proper data cleaning and transforming steps to prepare the data for loading into the model.

    Lessons

    • Data shaping
    • Enhance the data structure
    • Data Profiling

    Lab: Transforming and Loading Data

    • Loading Data

    After completing this module, students will be able to:

    • Apply data shape transformations
    • Enhance the structure of the data
    • Profile and examine the data

    Module 4: Design 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 tackle many of the common data modeling issues, including relationships, security, and performance.

    Lessons

    • Introduction to data modeling
    • Working with tables
    • Dimensions and Hierarchies

    Lab: Data Modeling in Power BI Desktop

    • Create Model Relationships
    • Configure Tables
    • Review the model interface
    • Create Quick Measures

    Lab: Advanced Data Modeling in Power BI Desktop

    • Configure many-to-many relationships
    • Enforce row-level security

    After completing this module, students will be able to:

    • Understand the basics of data modeling
    • Define relationships and their cardinality
    • Implement Dimensions and Hierarchies
    • Create histograms and rankings

    Module 5: Create Measures using DAX in Power BI

    This module introduces you to the world of DAX and its true power for enhancing 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

    • Lessons
    • Introduction to DAX
    • DAX context
    • 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 filter context
    • Use Time Intelligence functions

    After completing this module, students will be able to:

    • Understand DAX
    • Use DAX for simple formulas and expressions
    • Create calculated tables and measures
    • Build simple measures
    • Work with Time Intelligence and Key Performance Indicators

    Module 6: Optimise Model Performance

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

    Lessons

    • Optimise the model for performance
    • Optimise DirectQuery Models
    • Create and manage Aggregations

    After completing this module, students will be able to:

    • Understand the importance of variables
    • Enhance the data model
    • Optimise the storage model
    • Implement aggregations

    Module 7: Create Reports

    This module introduces you to the fundamental concepts and principles of designing and building a report, including selecting the correct visuals, designing a page layout, and applying basic but critical functionality. The important topic of designing for accessibility is also covered.

    Lessons

    • Design a report
    • Enhance the report

    Lab: Designing a report in Power BI

    • Create a live connection in Power BI Desktop
    • Design a report
    • Configure visual fields and format properties

    Lab: Enhancing Power BI reports with interaction and formatting

    • Create and configure Sync Slicers
    • Create a drillthrough page
    • Apply conditional formatting
    • Create and use Bookmarks

    After completing this module, students will be able to:

    • Design a report page layout
    • Select and add effective visualisations
    • Add basic report functionality
    • Add report navigation and interactions
    • Improve report performance
    • Design for accessibility

    Module 8: Create Dashboards

    In this module you will learn how to tell a compelling story through the use of dashboards and the different navigation tools available to provide navigation. You will be introduced to features and functionality and how to enhance dashboards for usability and insights.

    Lessons

    • Create a Dashboard
    • Real-time Dashboards
    • Enhance a Dashboard

    Lab: Designing a report in Power BI Desktop

    • Create a Dashboard
    • Pin visuals to a Dashboard
    • Configure a Dashboard tile alert
    • Use Q&A to create a dashboard tile

    After completing this module, students will be able to:

    • Create a Dashboard
    • Understand real-time Dashboards
    • Enhance Dashboard usability

    Module 9: Create Paginated Reports in Power BI

    This module will teach you about paginated reports, including what they are how they fit into Power BI. You will then learn how to build and publish a report.

    Lessons

    • Paginated report overview
    • Create Paginated reports

    Lab: Creating a Paginated report

    • Use Power BI Report Builder
    • Design a multi-page report layout
    • Define a data source
    • Define a dataset
    • Create a report parameter
    • Export a report to PDF

     

    After completing this module, students will be able to:

    • Explain paginated reports
    • Create a paginated report
    • Create and configure a data source and dataset
    • Work with charts and tables
    • Publish a report

    Module 10: Perform Advanced Analytics

    This module helps you apply additional features to enhance the report for analytical insights in the data, equipping you with the steps to use the report for actual data analysis. You will also perform advanced analytics using AI visuals on the report for even deeper and meaningful data insights.

    Lessons

    • Advanced Analytics
    • Data Insights through AI visuals

    Lab: Data Analysis in Power BI Desktop

    • Create animated scatter charts
    • Use the visual to forecast values
    • Work with Decomposition Tree visual
    • Work with the Key Influencers visual

     

    After completing this module, students will be able to:

    • Explore statistical summary
    • Use the Analyse feature
    • Identify outliers in data
    • Conduct time-series analysis
    • Use the AI visuals
    • Use the Advanced Analytics custom visual

    Module 11: Create and Manage Workspaces

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

    Lessons

    • Creating Workspaces
    • Sharing and Managing Assets

    Lab: Publishing and Sharing Power BI Content

    • Map security principals to dataset roles
    • Share a dashboard
    • Publish an App

     

    After completing this module, students will be able to:

    • Create and manage a workspace
    • Understand workspace collaboration
    • Monitor workspace usage and performance
    • Distribute an App

    Module 12: Manage Datasets in Power BI

    In this module you will learn the concepts of managing Power BI assets, including datasets and workspaces. You will also publish datasets to the Power BI service, then refresh and secure them.

    Lessons

    • Parameters
    • Datasets

     After completing this module, students will be able to:

    • Create and work with parameters
    • Manage datasets
    • Configure dataset refresh
    • Troubleshoot gateway connectivity

    Module 13: Row-level security

    The final module of the PL-300 course teaches you the steps for implementing and configuring security in Power BI to secure Power BI assets.

    Lessons

    • Security in Power BI

    After completing this module, students will be able to:

    • Understand the aspects of Power BI security
    • Configure row-level security roles and group memberships
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