Introduction to Analysing Data with Power BI

Description:

The main purpose of the course is to give students a good understanding of data analysis with Power BI. The course includes creating visualizations, the Power BI Service, and sharing dashboards.

Duration: 3 Days

 

5 Top Takeaways from the Course

Charts

  1. Make your existing data work harder for you
  2. Integrate diverse data stores to a single data model
  3. Transform raw data to business intelligence
  4. Create rich visualisation from raw data
  5. Share business intelligence with colleagues

At Course Completion:

After completing this course, students will be able to:

  • Perform Power BI desktop data transformation.
  • Describe Power BI desktop modelling.
  • Create a Power BI desktop visualization.
  • Implement the Power BI service.
  • Describe how to connect to Excel
  • Describe how to collaborate with Power BI data.
  • Connect directly to Azure data stores.
  • Download and use the Power BI mobile

Audience Profile:

The course will likely be attended by SQL Server report creators who are interested in alternative methods of presenting data.

Prerequisites:

  • Excellent knowledge of relational databases and reporting.
  • Some basic knowledge of data warehouse schema topology (including star and snowflake schemas).
  • Some exposure to basic programming constructs (such as looping and branching).
  • An awareness of key business priorities such as revenue, profitability, and financial accounting is desirable.
  • Familiarity with Microsoft Office applications – particularly Excel.

Topics:

Module 1: Power BI Desktop Data Transformations
This module describes how to import data into Power BI.
Lessons

  • What is Power BI?
  • Power BI data
  • Transformations

Lab: Import Data to Power BI

  • Import data to Power BI desktop
  • Import data from CSV files
  • Import data from a less structured file

After completing this module, students will be able to:

  • Describe what Power BI is and what it does.
  • Describe the types of data.
  • Perform data transformations.

Module 2: Power BI Desktop Modelling
This module introduces Power BI desktop modelling.
Lessons

  • Optimizing data models
  • Calculations
  • Hierarchies

Lab : Manage Power BI data

  • Manage table relationships.
  • Last year comparison
  • Year to date
  • Market share
  • Optimize the data model

After completing this module, students will be able to:

  • Optimize data models.
  • Perform calculations with Power BI data.
  • Describe and create hierarchies.

Module 3: Power BI Desktop Visualization
At the end of this module students will be able to create a Power BI desktop visualization.
Lessons

  • Visualizing your data
  • Working with multiple visualizations

Lab : Create reports with visualizations

  • Cross-tabular reports
  • Part-to-Whole reports
  • Relationship reports
  • Trend reports
  • Rank reports

After completing this module, students will be able to:

  • Visualize data using Power BI
  • Work with multiple visualizations.

Module 4: Power BI Service
This module describes how to implement the Power BI service.
Lessons

  • Working with the Power BI service
  • Configuring a dashboard
  • Viewing a Power BI Dashboard

Lab : Implementing the Power BI service

  • Upload a Power BI report
  • Share a Power BI dashboard
  • Configure data refresh

After completing this module, students will be able to:

  • Work with the Power BI service.
  • Configure a Power BI dashboard.
  • View a Power BI dashboard.

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