Microsoft Power BI

• Introduction to Power BI

  • • Business Intelligence
    • Self Service Business Intelligence
    • SSBI Tools
    • What is Power BI
    • Why Power BI?
    • Key Benefits of Power BI
    • Flow of Power BI
    • Components of Power BI
    • Architecture of Power BI
    • Building Blocks of Power BI

• Power BI Desktop

  • • Overview of Power BI Desktop
    • Data Sources in Power BI Desktop
    • Connecting to a data sources
    • Query Editor in Power BI
    • Clean and Transform your data with Query Editor
    • Combining Data ? Merging and Appending
    • Cleaning irregularly formatted data
    • Views in Power BI Desktop
    • Modelling Data
    • Manage Data Relationship
    • Cross Filter Direction
    • Create calculated tables and measures
    • Optimizing Data Models

• Data Analysis Expressions (DAX)

  • • Essential concepts in DAX
    • Why is DAX important?
    • DAX Syntax
    • Data Types in DAX
    • Calculation Types
    • DAX Functions
    • Measures in DAX
    • DAX Operators
    • DAX tables and filtering
    • DAX queries
    • DAX Parameter Naming

• Data Visualization

  • • Introduction to visuals in Power BI
    • Charts in Power BI
    • Matrixes and tables
    • Slicers
    • Map Visualizations
    • Gauges and Single Number Cards
    • Modifying colors in charts and visuals
    • Shapes, text boxes, and images
    • What Are Custom Visuals?
    • Page layout and formatting
    • KPI Visuals
    • Z-Order

• Direct Connectivity

  • • Introduction to using Excel data in Power BI
    • Exploring live connections to data with Power BI
    • Connecting directly to SQL Azure, HD Spark, SQL Server Analysis Services/ My SQL
    • Introduction to Power BI Development API
    • Import Power View and Power Pivot to Power BI
    • Power BI Publisher for Excel
    • Content packs
    • Introducing Power BI Mobile

• Power BI Report Servers

  • • Report Server Basics
    • Web Portal
    • Paginated Reports
    • Row level Security
    • Data Gateways
    • Scheduled Refresh
    • Resources (Rest API/ SOAP APIs/ URL Access)

• Advanced Analytics in Power BI using R & Python

  • • R Integration in Power BI Desktop
    • R visuals in Power BI
    • R Powered Custom Visuals
    • Creating R visuals in Power BI
    • R Visuals in Power BI Service
    • R Scripts Security
    • Creating visual using Python

• In-class Project

  • • Learners will be required to create an exhaustive project where they?ll be required to incorporate all their learnings of Power BI.

• Lesson 01- Course Introduction

  • • Welcome to Power BI Course

    •  Skills Covered

    • Business Intelligence and Data Analytics High level Overview

    •  Introduction to Power BI

    •  Different Power BI Offerings

    • Installing Power BI

• Lesson 02 - Get Data From Different Data Source

  • • Identify and Connect to a Data Source

    • Change Data Source Settings

    •  Select a Shared Dataset

    • Select a Storage Mode

    •  Choose an Appropriate Query Type

    • Use Microsoft Dataverse

    •  Use Parameters

    •  Use or Create a PBIDS file

• Lesson 03 - Profile the data

  • •  Identify Data Anomalies

    • Examine Data Structures

    •  Interrogate Column Properties

    • Interrogate Data Statistics

• Lesson 04 - Clean Transform and Load The data

  • • Resolve Inconsistencies Unexpected or Null Values and Data Quality Issues

    •  Apply User friendly Value Replacements

    • Evaluate and Transform Column Data Types

    • Apply Data Shape Transformations to Table Structures

    • Combine Queries

    •  Apply User friendly Naming Conventions to Columns and Queries

    •  Leverage Advanced Editor to Modify Power Query M code

• Lesson 05 - Design a Data Model

  • • Define the Tables

    •  Configure Table and Column Properties

    •  Flatten out a Parent child Hierarchy

    •  Define Role playing Dimensions

    •  Create a Common Date Table

• Lesson 06 - Develop a Data Model

  • • Apply Cross filter Direction and Security Filtering

    • Create Calculated Tables

    • Create Calculated Columns

    •  Implement Row level Security Roles

    •  Set up the Q and A Feature

• Lesson 07 - Optimize Model Performance

  • • Remove Unnecessary Rows and Columns

    •  Identify Poorly Performing Measures Relationships and Visuals
    •  Improve Cardinality Levels

    •  Optimize DirectQuery Models

    •  Create and Manage Aggregations

    •  Use Query Diagnostics

• Lesson 08 - Create Report

  • • Add Visualization Items to Reports

    • Choose an Appropriate Visualization Type

    •  Format and Configure Visualizations

    •  Apply Slicing and Filtering

    •  Add an R or Python Visual

• Lesson 09 - Create Dashboard

  • • Set Mobile View

    • Manage Tiles on a Dashboard

    • Configure Data Alerts

    •  Use the Q and A Feature

    •  Add a Dashboard Theme

    • Pin a Live Report Page to a Dashboa

• Lesson 10 - Enhance Report to Expose Insight

  • • Perform Top N Analysis

    •  Explore Statistical Summary

    •  Use the Q and A Visual

    • Add a Quick Insights Result to a Report

    •  Use the Play Axis Feature of a Visualization

    •  Personalize Visuals

• Lesson 11 - Perform Advance Analysis

  • • Identify Outliers

    •  Conduct Time Series Analysis

    •  Use Groupings and Binnings

    •  Use the Key Influencers to Explore Dimensional Variances

    • Use the Decomposition Tree Visual to Break Down a Measure

    •  Apply AI Insights

• Lesson 12 - Manage Datasets

  • • Configure a Dataset Scheduled Refresh

    • Configure Row level Security Group Membership

    •  Configure Incremental Refresh Settings

    • Promote or Certify Power BI Datasets