Power BI Certification Training

About Course

The Power BI Certification Training Course equips learners with the skills to analyze data, create interactive dashboards, and generate meaningful business insights using Microsoft Power BI. The course covers key concepts such as Power BI Desktop, Power BI Service, data modeling, DAX functions, Power Query, and data visualization techniques. Learners gain hands-on experience in connecting to various data sources, transforming raw data into reports, and publishing dashboards for collaboration. Designed for business analysts, data professionals, and aspiring BI experts, this training helps participants master end-to-end business intelligence workflows and prepares them for the official Power BI certification exam.As of my last update, Microsoft does not offer a certification specifically named “PL-300” for Power BI Data Analyst Associate. Typically, Microsoft Power BI certifications fall under the following categories: DA-100 for Data Analyst Associate and DP-203 for Data Engineer Associate. These certifications validate skills in data analysis, visualization, and data engineering using Microsoft Power BI tools and services, preparing professionals for roles in data analysis, business intelligence, and data engineering. They demonstrate proficiency in leveraging Power BI to analyze data, create visualizations, and derive insights to drive business decisions effectively.

Course Content

Module 1 – INTRODUCTION TO POWER BI

1.1 Introduction to Business Intelligence (BI)
1.2 Stages of business intelligence (BI)
1.3 Use cases of BI
1.4 Various BI tools
1.5 Overview of Data warehouse & concepts
1.6 Introduction to Power BI
1.7 Why Power BI
1.8 Power BI Components
1.9 Power BI pricing structure
1.10 Building blocks of Power BI
1.11 Architecture of Power BI
1.12 Power BI vs Tableau vs QlikView
1.13 Introduction of Power BI Desktop
1.14 Installation of Power BI Desktop
1.15 The key features of Power BI workflow
1.16 Process of creating reports in Power BI

Module 2 – DATA EXTRACTION

2.1 Overview of Power BI desktop
2.2 Data sources in Power BI
2.3 Using files (excel, pdf, csv, etc.) as a data source
2.4 Using SaaS connectors
2.5 Extracting data from folders, and databases
2.6 Working with Azure SQL database and database sources
2.7 Connecting to Analysis Services
2.8 Other data sources (OData, web, SharePoint etc.)
2.9 Python & R script in Power BI
2.10 Introduction of power query editor
2.11 Advance editor
2.12 Query dependency editor

Module 3 – DATA TRANSFORMATION – SHAPING & COMBINING DATA

3.1 Shaping data using Power Query Editor
3.2 Formatting data
3.3 Transformation of data
3.4 Understanding of Data types
3.5 Data profiling for data quality check
3.6 Naming conventions & best practices to consider
3.7 Identify and create appropriate keys for joins
3.8 Working with Parameters
3.9 Merge Query
3.10 Append Query
3.11 Group by of data (aggregation of data)
3.12 Applied steps (query settings)
3.13 Duplicate & Reference tables
3.14 Transpose of data
3.15 Fill
3.16 Pivot & Un-pivot of data
3.17 Custom columns
3.18 Conditional columns
3.19 Replace data from the tables
3.20 Split columns values
3.21 Move columns & sorting of data
3.22 Detect data type, count rows & reverse rows
3.23 Promote rows as column headers
3.24 Hierarchies in Power BI
3.25 M query

Module 4 – DATA MODELLING & DAX

4.1 Introduction of relationships
4.2 Creating relationships
4.3 Cardinality
4.4 Cross filter direction
4.5 Use of inactive relationships
4.6 Introduction of DAX
4.7 Why DAX is used
4.8 DAX syntax
4.9 DAX functions
4.10 Context in DAX
4.11 Calculated columns using DAX
4.12 Measures using DAX
4.13 Calculated tables using DAX
4.14 Learning about table, information, logical, text, iterator,
4.15 Time intelligence functions (YTD, QTD, MTD)
4.16 Cumulative values, calculated tables, and ranking and rank over groups
4.17 Date and time functions
4.18 identify poorly performing measures, relationships, and visuals
4.19 DAX advanced features

Module 5 – DATA VISUALIZATION WITH ANALYTICS

5.1 Deep dive into Power BI data visualization
5.2 Understanding Power View and Power Map
5.3 Data visualization techniques
5.4 Page layout & Formatting
5.5 Power BI Desktop visualization
5.6 Formatting and customizing visuals
5.7 Visualization interaction
5.8 Custom visualization in Power BI
5.9 Top-down and bottom-up analytics
5.10 Drill down
5.11 Drill through
5.12 Page navigations
5.13 Bookmarks
5.14 Selection pane to show/hide visuals
5.15 Comparing volume and value-based analytics
5.16 Combinations charts (dual axis charts)
5.17 Filter pane
5.18 Slicers
5.19 Use of Hierarchies in drill down analysis
5.20 Theme for corporate standards
5.21 Power BI template for design reusability
5.22 Mastering the best practices
5.23 Performance analyzer in Power BI for monitoring performance of report
5.24 Power BI Q&A (Natural Language Query visual)
5.25 Sync slicers
5.26 Tooltips & custom tooltips
5.27 Tables & matrix
5.28 Conditional formatting on visuals
5.29 Waterfall chart, KPI, Donut chart, Scatter chart
5.30 Geographical data visualization using Maps

Module 6 – POWER BI SERVICE (Cloud), Q & A AND DATA INSIGHTS

6.1 Introduction to Power BI Service
6.2 Introduction of workspaces
6.3 Dashboard
6.4 Creating & Configuring Dashboards
6.5 Dashboard theme
6.6 Reports vs Dashboards
6.7 Building workspace Apps
6.8 Sharing reports & dashboards
6.9 configure subscriptions and data alerts
6.10 Paginated report
6.11 Introduction to Power Q & A
6.12 Ask questions about your data using Natural Query Language
6.13 Getting answers in the form of charts, graphs, and data discovery methodologies
6.14 Configure custom questions for Q&A like FAQ
6.15 Ad-hoc analytics building
6.16 Power Q&A best practices
6.17 Quick Insights
6.18 Subscribe, Alerts, Usage statics, Related content
6.19 Design reports on Power BI Service
6.20 Collaboration using Power BI Service
6.21 Row Level Security (RLS)
6.22 Introduction of Paginated Reports
6.23 Introduction of Power BI Report Server

Module 7 – POWER BI SETTINGS, ADMINISTRATION & DIRECT CONNECTIVITY

7.1 Getting to understand Power BI Desktop settings
7.2 Aggregating data from multiple data sources
7.3 Power BI Service settings
7.4 Power BI Admin Portal
7.5 Administration activities
7.6 Power BI usage analysis
7.7 Introduction of Office 365 admin activities
7.8 Introduction of Data Gateway
7.9 Installation & Configuration of data gateways
7.10 Scheduling auto data refresh
7.11 Managing groups, row-level security, datasets, reports, and dashboards
7.12 Real time data analysis using Direct Connectivity
7.13 Direct Query vs Import Mode

Module 8 – EMBEDDED POWER BI WITH API & POWER BI MOBILE

8.1 Introduction to embedded Power BI
8.2 Create embedded code
8.3 Manage embedded code
8.4 Integration of Power BI in SharePoint
8.5 Introduction of Power BI API
8.6 Power BI Embedded playground
8.7 Introduction to Power BI Mobile
8.8 Creating mobile based reports & dashboards
8.9 Optimizing report for Power BI mobile app
8.10 Features of Power BI mobile app
8.11 Introduction of integrating Power BI & Excel
8.12 Power BI Analyze in Excel

Module 9 – POWER BI ADVANCE & POWER BI PREMIUM

9.1 Introduction of Power BI Premium
9.2 Power BI Premium per user
9.3 Power BI Premium features
9.4 Introduction to Data Flow
9.5 Create Data Flow
9.6 Advantages of Data Flow
9.7 Create reports using Data Flow
9.8 Introduction to Power BI Deployment Pipelines
9.9 Create Deployment Pipelines
9.10 Benefits of Deployment Pipelines
9.11 Introduction of Sensitivity Labels
9.12 Introduction of Power BI Goals feature
9.13 Incremental data load in Power BI
9.14 use AI visuals
9.15 use the Forecast feature
9.16 Power BI best practice rules to improve performance

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About Course

What Will You Learn?

Course Content

Module 1 – INTRODUCTION TO POWER BI

1.1 Introduction to Business Intelligence (BI)

1.2 Stages of business intelligence (BI)

1.3 Use cases of BI

1.4 Various BI tools

1.5 Overview of Data warehouse & concepts

1.6 Introduction to Power BI

1.7 Why Power BI

1.8 Power BI Components

1.9 Power BI pricing structure

1.10 Building blocks of Power BI

1.11 Architecture of Power BI

1.12 Power BI vs Tableau vs QlikView

1.13 Introduction of Power BI Desktop

1.14 Installation of Power BI Desktop

1.15 The key features of Power BI workflow

1.16 Process of creating reports in Power BI

Module 2 – DATA EXTRACTION

2.1 Overview of Power BI desktop

2.2 Data sources in Power BI

2.3 Using files (excel, pdf, csv, etc.) as a data source

2.4 Using SaaS connectors

2.5 Extracting data from folders, and databases

2.6 Working with Azure SQL database and database sources

2.7 Connecting to Analysis Services

2.8 Other data sources (OData, web, SharePoint etc.)

2.9 Python & R script in Power BI

2.10 Introduction of power query editor

2.11 Advance editor

2.12 Query dependency editor

Module 3 – DATA TRANSFORMATION – SHAPING & COMBINING DATA

3.1 Shaping data using Power Query Editor

3.2 Formatting data

3.3 Transformation of data

3.4 Understanding of Data types

3.5 Data profiling for data quality check

3.6 Naming conventions & best practices to consider

3.7 Identify and create appropriate keys for joins

3.8 Working with Parameters

3.9 Merge Query

3.10 Append Query

3.11 Group by of data (aggregation of data)

3.12 Applied steps (query settings)

3.13 Duplicate & Reference tables

3.14 Transpose of data

3.15 Fill

3.16 Pivot & Un-pivot of data

3.17 Custom columns

3.18 Conditional columns

3.19 Replace data from the tables

3.20 Split columns values

3.21 Move columns & sorting of data

3.22 Detect data type, count rows & reverse rows

3.23 Promote rows as column headers

3.24 Hierarchies in Power BI

3.25 M query

Module 4 – DATA MODELLING & DAX

4.1 Introduction of relationships

4.2 Creating relationships

4.3 Cardinality

4.4 Cross filter direction

4.5 Use of inactive relationships

4.6 Introduction of DAX

4.7 Why DAX is used

4.8 DAX syntax

4.9 DAX functions

4.10 Context in DAX

4.11 Calculated columns using DAX

4.12 Measures using DAX

4.13 Calculated tables using DAX

4.14 Learning about table, information, logical, text, iterator,

4.15 Time intelligence functions (YTD, QTD, MTD)

4.16 Cumulative values, calculated tables, and ranking and rank over groups

4.17 Date and time functions

4.18 identify poorly performing measures, relationships, and visuals

4.19 DAX advanced features

Module 5 – DATA VISUALIZATION WITH ANALYTICS