IT professionals (legacy tech)
- Currently working in IT
- Experience in Java, .NET, Salesforce, DBA or Testing
DP-700 Microsoft certification track
Master Data Engineer Azure · Microsoft Fabric & Power BI
A 100-hour, two-program journey from SQL fundamentals to production-grade Azure and Microsoft Fabric pipelines — built by a 15-year IT veteran and taught through live sessions, real sprints and two end-to-end projects.
Trainer
Ram
IT experience
15+ years
Training experience
10+ years
Duration
100 hours
Live demo
Sat, 10 AM
Call
79974 57228
Free live demo
Every Saturday, 10 AM
Ram Boyapati
Lead Trainer · Azure, Microsoft Fabric & Power BI
Who should join
Four types of professionals transforming their careers
No matter where you're starting from, there's a clear path in.
Non-IT professionals
- Facing low salary growth
- Roles being impacted by AI & automation
Career gap candidates
- Just after graduation
- Preparing for govt. exams or running a business
Career break (0.5–1 year)
- Returning after layoffs or family reasons
- From an IT or non-IT background
Cloud technologies
Data pipelines
Analytics & insights
AI-powered future
Career roadmap
Your step-by-step journey to becoming an Azure Fabric Data Engineer
-
Program 1: Training
- Azure Data Engineering
- Microsoft Fabric Data Engineering
- Power BI
-
Program 2: Placement assistance
- Hands-on tasks
- Two end-to-end projects
- Interview preparation
- Mock interviews & resume prep
-
Certification (DP-700)
- Microsoft-certified path
- Guided exam preparation
-
Interview opportunities
- Real interview calls
- Direct job opportunities
-
Work support
- Real-time project support
- On-job assistance
Program structure
The course contains two programs
Learn the stack first, then apply it the way a delivery team does.
Data Engineering Training
For beginners and professionals building Azure, Fabric and Power BI skills, delivered as daily live sessions.
- Live classes + recordings
- Hands-on practice
- Resume templates
- DP-700 guidance
- 3 years LMS access
Real-Time Industry Experience
Practical exposure to real-world scenarios for stronger applied skills, run like an actual delivery team.
- Agile 10-sprint model
- 150+ real tasks
- 2 end-to-end projects
- Interview prep
- Mock interviews + resume prep
Curriculum map
Five modules. Two full service stacks.
Build the skills required to become a job-ready Data Engineer.
Module 01
SQL
Build a strong foundation in SQL and relational databases.
SQL basicsJoinsAnalytical functions
Module 02
Python
Learn the Python programming required for modern data engineering.
Python basicsDataFramesSpark notebooks
Module 03
Azure Data Engineering
Build real-world data pipelines using Microsoft Azure.
Data Lake Gen2Data FactorySynapseDatabricks
Module 04
Microsoft Fabric Data Engineering
Work with Microsoft's modern unified data platform.
OneLakeLakehouseDataflow Gen2Warehouse
Module 05
Microsoft Fabric & Power BI
Transform data into business-ready analytics and dashboards.
Semantic modelsVisualizationsData Agents
Full syllabus
Topic-by-topic breakdown
Every session mapped out — from your first storage account to a deployed Fabric project.
- Data Engineering demo roadmap
- How to create a subscription for Azure and Fabric
- How to create storage services / Storage Account
- Blob vs Data Lake Gen2
- Medallion architecture & advanced storage account features
- Install SQL Server & SQL Database in Azure & Synapse
- Data warehouse concepts
- Synapse Dedicated Pool DWH in Azure
- Introduction to Data Factory in Azure & Fabric
- Copy data: blob to blob & blob to Azure SQL DB
- Copy data blob to blob — copy behavior
- Copy multiple files into multiple / single tables
- Copy data from on-prem SQL to Blob, multiple tables into multiple files
- If file exists, copy — else send email
- If file exists, copy — else wait until file is placed, using Until
- What is incremental loading & how to implement it
- Data Flow transformations in Data Factory (Day 1)
- Data Flow transformations in Data Factory (Day 2)
- Scheduling triggers in Data Factory
- Introduction to Databricks
- Spark architecture
- SQL basics
- Python basics
- RDD, DataFrame & Dataset
- Types of transformations and actions
- String & aggregate transformations on DataFrames
- Joins & analytical functions
- How to read & write files from DBFS
- Connecting to Data Lake Gen2 & Azure SQL
- Azure Key Vault & parameterization in Databricks
- Delta Lake & Delta Live Tables
- SCD implementation in Delta Lake
- Unity Catalog in Databricks
- Workflows in Databricks
- Performance optimization
- What is a Git repo
- Deployment of Data Factory, Databricks & Power BI reports
- Complete flow design in Azure & Fabric
- What is OneLake & Lakehouse medallion architecture
- How to create shortcuts
- SQL Database & Warehouse in Fabric
- Introduction to Data Factory in Fabric
- Copy data Lakehouse to Lakehouse & Lakehouse to Azure SQL DB
- Copy data Lakehouse to Lakehouse — copy behavior
- Copy multiple files into multiple / single tables
- Copy data from on-prem SQL to Lakehouse, multiple tables to multiple files
- If file exists, copy — else send email
- If file exists, copy — else wait until file is placed, using Until
- Incremental loading & implementation
- Scheduling Data Factory & data pipelines
- Transformations in Data Flow Gen2 (Day 1 & Day 2)
- Copy data from Lakehouse to Warehouse using Data Flow Gen2
- Introduction to Notebooks & Spark
- RDD, DataFrame & Dataset
- Transformations & actions, string/aggregate ops, joins & analytical functions
- Read & write files from Lakehouse
- Delta Lake & Delta Live Tables
- SCD implementation & performance optimization
- Scheduling notebooks using jobs & data pipelines
- Write data into warehouse using T-SQL in notebooks
- Introduction to Power BI & installing Power BI Desktop
- Semantic modeling in Fabric & Power BI
- Designing visualizations in Power BI
- Developing Data Agents in Fabric
- Deployment of the project
- Complete project flow design in Fabric
Capstone work
Two end-to-end projects
Real-world solutions, end-to-end implementation, business impact — one in Fabric, one in Azure.
Project 1 · Microsoft Fabric
Health Care Insurance
Analytics for better decisions and improved outcomes.
Total claims
48,540
Claim amount
₹125.6 Cr
Approved claims
36,425
Approval rate
75.1%
Pipeline
- Data ingestion
- Data Lake
- Data processing
- Data warehouse
- Analytics & reports
Project 2 · Microsoft Azure
Retail Sales
Drive growth with data-powered retail intelligence.
Total sales
₹245.8 Cr
Total orders
1.2M
Avg. order value
₹2,045
Gross margin
28.6%
Pipeline
- Data sources
- Ingestion
- Processing
- Storage
Real outcomes
From different backgrounds to high-paying Data Engineer roles
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Bhargavi
Placed · Top MNC
IT → Data Engineer · 13+ yrs · upskilled to Azure Fabric Data Engineering
₹16 LPA
₹28 LPA
Anusha
Placed
Non-IT → Data Engineer · 4+ yrs · upskilled to Data Engineering
₹5.5 LPA
₹9 LPA
Pavan
Placed
Database Developer → Data Engineer · 12 yrs · upskilled to Data Engineering
₹22 LPA
Higher growth potential
Niharika
Placed
Azure Admin → Data Engineer · 6 yrs · upskilled to Data Engineering
₹9 LPA
₹17 LPA
Program overview
Everything the course includes, at a glance
100
Total hours
60
Hrs — Program 1
40
Hrs — Program 2
5
Modules
150+
Real-time tasks
9
Structured sprints
Get in touch
Talk to our team
Call, visit us at KPHB, or send the form — we'll get back to you shortly.
Phone+91 79974 57228
Websiteeclasess.com
Address3rd Floor, Alluri Trade Center, Near KPHB Metro Station, KPHB, Hyderabad 500072
Free live demoEvery Saturday, 10 AM
Request a call back
Fill out the form and our team will contact you shortly.