Power BI with Python


Course Duration & Payment Details

Days: Saturday and Sunday only
Timing: 08:00 to 10:00pm
Duration: 24 hours
Starting from: Sunday, 15 May 2022
Last date of registration: Tuesday, 10 May 2022

Actual Fee: 20,000/-  | Early bird discount: 10,000/-
How to Pay: Online Payment
Bank: Habib Bank Limited
Title: Irfan
Account No: 11557900292501 | PK02HABB0011557900292501

Training Highlights

Getting started

  • What is BI?
  • What is Self Service BI and the steps involved?
  • Overview of Power BI
  • Different products of Power BI
  • Power BI licensing and features
  • Power BI pros and cons
  • Other self-service BI tools and comparison

Data Visualization in Power BI Desktop

  • Visualization Best Practices
  • Which Chart is the Best?
  • Basic Charts
  • Interaction of Visuals
  • Color Formatting
  • Setting Sort Order
  • Dynamic Tooltips in visualizations
  • Slicers & Timeline Slicers
  • Cross Filtering and Highlighting
  • Visual, Page, and Report Level Filters
  • Drill Down/Up & Drill Through
  • Hierarchies
  • KPI Visuals
  • Working with Map Visuals
  • Table and Matrix with Conditional Formatting
  • Multiple levels of filters
  • Using custom slicers
  • Switch between web/phone layout
  • Inserting shapes, images, and text boxes
  • Hyperlink & Bookmark
  • Using interactive buttons
  • The Key Influencers Visual
  • Artificial Intelligence (AI) Visuals
  • Working with Custom Visuals

Data Transformation / Edit Queries

  • What is Power Query?
  • Basic Transformations
  • Get Data from SQL, CSV, TXT, Excel & Web

Combine Queries

  • Merge, Joining queries
  • Append, creating a big list
  • Combine Binaries; Looping through files in a folder


  • Column Operations
  • Row Operations
  • Filtering & Sorting
  • Group By
  • Transpose
  • Pivot, Unpivot
  • Split & Merge
  • Date Transformations (Year, Month, Quarter)
  • Extending Fiscal Date Column
  • Aggregate
  • Add Custom Column

Power Query Formula Language: M

  • What is M? and the importance of learning M
  • M Syntax
  • Examples of M

Working with AI (Premium Services) Visuals

Data Modeling

  • Introduction to relationship view navigation
  • Understanding data modeling concepts
  • Creating and editing relationships
  • Why is a data model more efficient?
  • Relationship-based on multiple Columns
  • Cardinality: Many-to-One & One-to-One & One-to-Many
  • Understanding how LEFT, RIGHT, INNER, and OUTER joins work
  • Cross Filter Direction & Many-to-Many
  • Managing Active vs. Inactive Relationships

Date & Time Functions – Calendar, CalendarAuto, Date, Day, Month, Year, Format, Datediff, Now, Today, Weekday, Weeknum

Filter Functions – All, AllExcept, AllSelected, Calculate, Filter, HasOneValue, Related

Logical Functions – IF, Switch

Time Intelligence Expressions – MTD, QTD, YTD, Running Total

Statistical Function – Average, AverageX, Count, CountA, CountBlank, CountRows, CountX, Max, MaxX, Min, RankX, Sumarize

  • Top N Values, Top N Filter, Top Order calculations, Top 10 Customers, Dynamic

Power BI service

  • What are workspaces?
  • Difference between datasets, workbooks, reports, and dashboards
  • Publishing data to web
  • Pinning visuals and creating dashboards
  • Viewing reports & dashboards
  • Sharing reports & dashboards
  • Row-level security


  • What is Gateway?
  • Types of Gateway
  • On-premises Gateway in Details
  • Installation, Configuration, and considerations
  • Schedule Refresh

Paginated Reports

  • What is Paginated Report in Power BI
  • When to use Paginated Report?
  • Prerequisites and Tools needed to get started
  • Create Power BI Premium Workspace
  • Interface of Power BI Report Builder
  • Connect SQL Data source in Power BI Paginated Report
  • Create the first report on Report Builder
  • Publish to Power BI Service
  • Install Data Gateway
  • Manage Gateway

Creating the live streaming dataset in Power BI

Working with Python Visuals in Power BI

  • Installation Anaconda
  • Data Frame Functions
  • Enabling Python in Power BI
  • Importing data using a Python Script
  • Working with Python libraries – Pandas & Matplotlib
  • Working with variables
  • Using a Python script to Create Visualizations in Power BI