Power BI Complete

Audience

This 4-day course is intended for anyone who is new to designing and implementing self-service Business Intelligence (BI) solutions using Microsoft Power BI Desktop and the Power BI Service. It is ideal for anyone who needs a total immersion in the subject matter as the course structure is very comprehensive.

The training is delivered with plenty of illustrated examples and augmented with practical hands-on exercises to enhance the learning experience. Also, as Power BI Desktop and the Power BI Service are continually evolving, this course is regularly reviewed and updated to keep the delivered content as fresh and relevant as possible, thus ensuring maximum productivity from the learning experience.

Due to the very comprehensive nature of this course, the content delivered may vary depending on new and updated features, delegate requirements, and course objectives.

Prerequisites

There are no specific technical prerequisites for this course, but a familiarity with Excel and/or relational database technologies may prove beneficial. The main consideration is to have a basic understanding of your business needs to collect, cleanse, and analyse data, in order to be able to visualise and gain insights into that data.

Course Objectives

The first part of the course introduces the capabilities and components of Power BI Desktop before delving into the realms of discovering and loading data from a variety of sources.

Primarily focussed on using Power Query to create queries for implementation in data models, students will learn how to shape and transform loaded data, mashup data from various sources by merging and appending data, and manage, structure, and parameterise queries.

Delving behind the scenes, students will also be introduced to the M language, highlighting ways in which existing code can be tweaked and how user defined code and functions can be implemented.

Part two of the course introduces students to tabular data modelling concepts, preparing the data in readiness for use in reports and dashboards. The importance of implementing relationships is also covered.

In order to enhance the data model, students will be introduced to the DAX expression language to enable them to implement calculated columns, measures, and tables. Consideration is also given to implementing time intelligence in the design of data models.

In part three, you will learn how to create and design reports and implement visualisations. We will first look at text-based visuals before moving on to graphical components like charts, gauges and KPIs (Key Performance Indicators).

The implementation of maps in reports is also given coverage. To create interactivity in reports, students will also learn how to implement various types of filters and slicers.

Finally, in part four, we turn our attention to the Power BI Web Service. Attendees will learn how to publish reports to the Power BI Service and how to organize and secure content.

The creation and use of dashboards will be considered, and the sharing of content will also be given coverage. We will look at user accessibility issues and consider how users, including mobile users, can interact with report content. Managing and refreshing datasets in the Power BI Service is also included.

This course is commensurate with the PL-300: Microsoft Power BI Data Analyst course, and serves as ideal preparation for the Microsoft PL-300 exam. In addition to providing the knowledge required for this exam, this course takes a broader and more practical approach to Power BI, demonstrating useful techniques that will prove extremely helpful in the workplace.

Upon successful completion of this course, students will be able to:

• Understand the Role Power BI plays in Self-Service BI

• Understand the Constituent Parts of Power BI Desktop

• Discover and Load Various Types of Data

• Shape and Transform Datasets

• Mashup Data

• Parameterise Queries

• Implement a Tabular Data Model

• Create and Manage Relationships

• Gain an Understanding of DAX

• Implement Calculated Columns and Measures

• Implement Time Intelligence

• Create Reports with Text-Based Visualisations

• Implement Conditional Formatting

• Create and Implement Charts

• Implement Gauges and KPIs

• Implement Maps

• Implement Filters

• Implement Slicers

• Analyse Visualization Performance

• Analyse Data with Advanced Visuals

• Understand the Role of the Power BI Service

• Publish Reports and Create Dashboards

• Manage and Secure Content in the Power BI Service

• Enhance the Report Consumer Usability Experience

• Create and Distribute Apps

Course Content

Part 1: Introduction and Power Query

Introducing Power BI

• Explore the Different Roles in Data

• Identify the Tasks Performed by a Data Analyst

• Describe the Power BI Products and Services

• Introducing Power BI Desktop

Loading Data

• Load Data from Text and Excel Files

• Load Data from Relational Databases

• Import, DirectQuery, and Connect Live Modes

• Composite Mode

• Load Data from OneDrive and SharePoint

• Load Data from Microsoft Dataverse

• Load Data from the Internet

• Connect to a Published Dataset

• Connect to a Dataflow

Transforming Data

• Profile Data

• Cleanse Data

• Shape Datasets

• Transform Datasets

• Query Folding

• Merge and Append Data

• Fuzzy Lookups

• Structure and Manage Queries

• View Query Dependencies

• Power Query Parameters

• Power BI Template Files

• Introduction to the M Language

• Create a User Defined Function with M

• Get the Time of the Last Data Refresh

• Part 2: Data Modelling and DAX

Data Modelling

• Basic Data Modelling Concepts

• Fact and Dimension Tables

• Configure Table and Column Properties

• Categorise Data

• Sorting Columns

• Organise Content with Display Folders

• Create and Manage Relationships

• Understand Filter Propagation

The DAX Expression Language

• Introduction to DAX

• Extend the Data Model with Calculated Columns

• Add Measures to the Data Model

• Implicit v Explicit Measures

• Quick Measures

• Manipulate the Filter Context with CALCULATE

• Create Calculated Tables

• Use Variables

• Create a Date Table

• Analyse Data over Time (Time Intelligence)

• Optimise the Storage Model

• Optimise DirectQuery Models

• Create and Manage Aggregations

• Part 3: Reports and Visuals

Visualising Data

• Implement and Format Table and Matrix Visuals

• Rename Fields in Visuals

• Show Items with no Data

• Conditionally Format Visual Content

• Use Card Visuals

• Implement and Format Charts

• Report Themes

• Use the Small Multiples Chart Option

• Sparklines

• Use Tooltips

• Implement Reports as Tooltips

• Implement and Use Hierarchies

• Group and Bin Data

• Continuous v Categorical Axis

• Custom Grouping

• Automatically Find Clusters of Data

• Animate Scatter Charts

• Use the Analytics Pane

• Forecasting & Anomaly Detection

• Use the Analyse Feature

• Tree Maps

• Gauges and KPIs

• Implement Maps

• Resolve Location Errors in Maps

• Implement Slicers

• Visual, Page, and Report Level Filters

• Synchronise Slicers across Pages

• Cross-Filtering and Cross-Highlighting

• Analyse the Performance of Visuals

• Part 4: Enhancing and Publishing Reports

Enhancing the User Experience

• Analyse Data with Decomposition Trees

• Analyse Data with Key Influencers

• Drillthrough Reports

• What-If Parameters

• Field Parameters

• Implement Bookmarks

• Implement Buttons

• Text Boxes, Shapes, and Images

• Page & Bookmark Navigation

• Show and Hide Content

• Implement and Manage Q&A

• Smart Narrative

• Custom Visuals and Slicers

• Scorecards & Power BI Metrics (aka Goals)

• Mobile Report Layout

The Power BI Web Service

• Introduction to the Power BI Web Service

• Publish Reports to the Power BI Web Service

• Manage and Organise Content in Workspaces

• Create and Manage Dashboards

• Dashboard Themes

• Set up Data Alerts

• Share Content and Workspaces

• Create and Distribute Apps

• Promote & Certify Content

• Sensitivity Labels

• Secure Data with Row Level Security (RLS)

• Object Level Security

• Refresh Datasets

• Understand Data Gateways

• Change Detection

• Incremental Refresh

• Quick Insights

• Analyse in Excel

• Export Reports

• Support for Paginated Reports in Power BI