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Comprehensive Power BI Training Course Content

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Learn Comprehensive Power BI Training Course Content

Cohort Based Learning – Only 10 Seats
40+ hours of live virtual training
New Age Curriculum with Gen AI tools
3 Real time projects and capstone project
Certification of completion

Why choose Hirekeyz ?

Curriculum

Industry relevant Curriculum

Training

Job-Ready Training

Projects

Capstone projects & case studies

Flexible

Flexible Learning

Team Working

Tools you will learn

NumPy

Matplotlib

Pandas

Excel

Power BI

AWS

Scikit-learn

SQL

Course Syllabus

Module 1: Introduction to Power BI (2 Hours)

What is Power BI?
Components of Power BI (Desktop, Service, Mobile, Report Server)
Power BI Architecture and Workflow
Installing Power BI Desktop
Overview of Power BI interface and features

Module 2: Getting Data in Power BI (3 Hours)

Data sources supported by Power BI (Excel, CSV, databases, web, etc.)
Connecting to data sources
Data import vs DirectQuery vs Live Connection
Using Power Query Editor for data ingestion and transformation
Basic data cleaning and shaping techniques

Module 3: Data Transformation and Modeling (5 Hours)

Introduction to Power Query Editor
Data transformation techniques (filtering, merging, appending)
Creating calculated columns and measures
Understanding data types and relationships
Building data models and managing relationships (1:1, 1:Many, Many:Many)
Star schema and Snowflake schema concepts in Power BI

Module 4: DAX Fundamentals (6 Hours)

What is DAX (Data Analysis Expressions)?
DAX syntax and operators
Calculated columns vs measures
Basic aggregation functions (SUM, AVERAGE, COUNT)
Logical functions (IF, SWITCH)
Time intelligence functions (DATEADD, SAMEPERIODLASTYEAR, TOTALYTD)
Filter functions (FILTER, ALL, RELATED)
Row context and filter context explained

Module 5: Visualizations in Power BI (6 Hours)

Overview of Power BI visualization types
Using charts: bar, column, line, pie, scatter
Cards, tables, and matrix visuals
Slicers and filters
Drill down and drill through functionality
Custom visuals: marketplace and import
Best practices for effective visualizations

Module 6: Power BI Service and Sharing (4 Hours)

Power BI Service overview
Publishing reports to Power BI Service
Creating and managing workspaces
Sharing reports and dashboards
Power BI Apps
Row-Level Security (RLS)
Data refresh settings and scheduling

Module 7: Advanced Analytics (4 Hours)

Using Quick Insights and AI visuals
Integrating Power BI with Azure ML
What-if parameters
Forecasting and clustering
Using Python and R scripts in Power BI

Module 8: Power BI Mobile and Embedded (2 Hours)

Power BI Mobile App overview
Creating mobile-optimized reports
Power BI Embedded basics for developers
Embedding reports in web apps

Module 9: Power BI Administration and Governance (3 Hours)

Power BI Admin Portal overview
Tenant settings and compliance
Audit logs and usage metrics
Managing user roles and licenses
Data governance best practices

Module 10: Real-Time Project - Retail Sales Analytics (8 Hours)

Project Overview and Data Understanding
Data ingestion and cleaning
Data modeling and relationship setup
Creating KPIs and measures using DAX
Designing interactive dashboards with slicers and filters
Publishing and sharing reports
Implementing Row-Level Security for different user roles
Final project presentation and review

Program Highlights

Experts

Learn from experts

Courses taught by experienced professors and industry professionals.

Certifications

Certification of Completion

Get the best of worlds Hirekeyz's certification.

Gen AI

New Age Curriculum

40+ Hours of learning of new tools, models and projects.

Learning Tools

Interactive Learning Tools

Access to videos, quizzes, and discussions for an engaging learning experience.

Affordable Fees

Affordable Tuition Fees

Access quality education without the high cost of traditional classrooms.

24/7 Access

24/7 Access to Study Material

Get access to recorded videos and assessments.

Who Should Do The Comprehensive Power BI Course?

Aspiring Analysts
Individuals looking to start a career in data analysis or analytics-related fields.
Career Changers
Professionals from non-technical backgrounds eager to transition into the high-demand field of data analytics.
IT & Engineering Graduates
Students or professionals with technical degrees who want to specialize in data analysis.
Business Professionals
Managers or executives aiming to make data-driven decisions and enhance business outcomes.
Freelancers & Consultants
Professionals who want to offer data analysis as a service to clients.
Upskilling Professionals
Those in adjacent fields like marketing, finance, or operations who want to add data analytics to their skill set.

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