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Microsoft Fabric Data Engineering Bootcamp Pune — Build production-grade Medallion Lakehouse with PySpark, DP-700 | MCAL Global
DP-700 Microsoft Certified Prep · 8 Modules · Capstone

Microsoft Fabric Data Engineering Bootcamp — Pune & Online

India’s most comprehensive Microsoft Fabric data engineering course. From Module 1, you build an end-to-end enterprise pipeline on Fabric — OneLake, PySpark, Eventstreams, and Purview — and every module adds a new, production-grade layer. DP-700 certification prep included. Classroom in Pune or live online across India.

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30 Hours · 8 Weekends Classroom, Pune & Live Online India
Microsoft Fabric OneLake PySpark Delta Lake Dataflows Gen2 Eventstreams Purview KQL

Microsoft Fabric Data Engineering Bootcamp — Key Facts

30 hrs

Hands-On Instruction
Production Labs

8+1

Modules + Capstone
Continuous Pipeline

DP-700

Certification Prep
Exam-Mapped Labs

Live

Classroom, Pune
Instructor-Led

“Microsoft Fabric is one of the most important data platform shifts since the introduction of cloud data warehouses. Engineers who understand its unified architecture will define the next decade of enterprise data.”

— Senior Data Architect, Microsoft Partner Network

MCAL vs Generic

MCAL Fabric Bootcamp vs Generic Online Courses

Here’s what sets MCAL apart from every other Fabric course in India.

MCAL Global Microsoft Fabric Data Engineering Bootcamp vs Generic Online Courses — Feature Comparison
Feature MCAL Bootcamp Generic Course
Hands-on Lakehouse Full enterprise architecture lab Conceptual only
Real-Time Pipeline Live ingestion with Eventhouse Rarely covered
DP-700 Prep Dedicated module + mocks Self-study only
Medallion Architecture Bronze → Silver → Gold Mentioned, not practiced
Enterprise Security RLS, CLS, Purview Skipped
Instructor Access Live Q&A, guided labs Pre-recorded
Capstone Project Full enterprise pipeline Toy datasets

8-Module Curriculum

Production-Grade, Session by Session

Fabric’s unified SaaS architecture and how it differs from traditional Azure services
OneLake shortcuts and cross-workspace data access patterns
Fabric Experiences: Lakehouse vs. Data Warehouse vs. Eventhouse — when to use which
Workspace governance, portal navigation, and capacity configuration

Lab: Provision a Fabric workspace, create a Lakehouse, configure OneLake folder structure and shortcuts

Pipeline Progress: Your Fabric workspace and OneLake infrastructure is live and configured

Fabric Data Factory Copy Activity for batch data ingestion from ADLS Gen2 and SQL databases
Dataflows Gen2 for no-code / low-code transformations and multi-destination outputs
REST API ingestion and Eventstreams for real-time streaming sources
On-Premises Data Gateway configuration and landing zone design patterns

Lab: Build a multi-source ingestion pipeline pulling from REST APIs, ADLS Gen2, and SQL into OneLake

Pipeline Progress: Multi-source data is flowing into your OneLake landing zone

Medallion architecture deep dive: Bronze, Silver, and Gold layer design with clear boundaries
Delta Lake table design with partition strategy, constraints, and data quality enforcement
V-Order optimization and Liquid Clustering for dramatically faster query performance
Enterprise Gotcha: Why naive partitioning kills Delta performance and how to avoid it

Lab: Design and deploy a three-layer Medallion Lakehouse with Delta tables and V-Order optimization

Pipeline Progress: Your Medallion Lakehouse is structured with governed Bronze, Silver, and Gold layers

PySpark transformation patterns: DataFrame API, Window functions, and broadcast joins
Incremental load patterns using Delta Lake MERGE / UPSERT and watermark columns
Notebook parameterization, error handling, logging, and unit testing strategies
Spark SQL on Lakehouses: when to use SQL vs. DataFrame API for optimal performance

Lab: Write a parameterized PySpark notebook that incrementally loads, transforms, and merges into Gold

Pipeline Progress: Your data is clean, optimized, and production-ready with automated transformations

Fabric Pipeline activities: Copy, Notebook, ForEach, If Condition, and Switch
Dynamic expressions and parameterized pipeline runs with runtime variables
Error handling with retry policies, failure paths, and alerting strategies
Cross-workspace pipeline invocation and scheduled triggering patterns

Lab: Build an orchestration pipeline with conditional logic, parameterized notebook calls, and scheduled runs

Pipeline Progress: Your pipeline runs automatically with scheduled orchestration and error recovery

Workspace roles and OneLake folder-level security configuration for team access control
Row-Level Security (RLS) and Column-Level Security (CLS) on semantic models
Microsoft Purview integration: data lineage, sensitivity labels, and automated scanning
Enterprise Gotcha: Compliance auditing patterns that satisfy real enterprise security reviews

Lab: Implement RLS on a semantic model, configure Purview lineage, and run a compliance audit

Pipeline Progress: Your pipeline is enterprise-hardened with multi-layer security and governance

Capacity Units (CUs) monitoring: reading the Monitoring Hub and spotting cost anomalies
Spark performance tuning: DAG analysis, caching strategies, and partition optimization
Delta table maintenance: OPTIMIZE, VACUUM, Z-ORDER — when and why for each
DirectLake mode: how it works, when it falls back, and how to optimize semantic models

Lab: Tune a Spark job using DAG analysis, run OPTIMIZE/VACUUM, and benchmark CU consumption

Pipeline Progress: Your pipeline is cost-efficient and performance-benchmarked for production workloads

Capstone architecture review: present your end-to-end enterprise pipeline to the class
DP-700 exam blueprint walkthrough: skill domains, question types, and time management
Mock exam scenarios covering the trickiest Fabric concepts and common exam traps
Lab-to-exam mapping: how every lab you completed maps to DP-700 skill objectives

Lab: Present your capstone architecture, complete mock exam scenarios, and map labs to DP-700 domains

Pipeline Progress: Complete — you are interview-ready and certification-ready

After This Bootcamp

Job-Ready Engineering Outcomes

Design and deploy a production-grade Medallion Lakehouse on Microsoft Fabric using Delta Parquet with V-Order optimization

Build multi-source ingestion pipelines using Fabric Data Factory, Dataflows Gen2, Eventstreams, and REST API connectors

Write production-quality PySpark and Spark SQL notebooks with error handling, logging, and incremental load patterns

Architect real-time data ingestion using Eventstreams and Eventhouse (KQL Database) for streaming analytics

Implement enterprise orchestration using Fabric Pipelines with dynamic parameters, conditional logic, and retry policies

Apply RLS, CLS, and Microsoft Purview for governed, audit-ready data solutions with full lineage tracking

Perform Spark DAG analysis, CU monitoring, and Delta maintenance (OPTIMIZE, VACUUM, Z-ORDER) for performance tuning

Confidently sit for — and pass — the DP-700: Microsoft Certified Fabric Data Engineer Associate exam

Tools & Technologies

What You Will Master

Microsoft Fabric OneLake Apache Spark PySpark Delta Lake Fabric Data Factory Dataflows Gen2 Eventstreams KQL / Eventhouse Microsoft Purview Power Query (M) Spark SQL DirectLake Mode V-Order / Z-ORDER DP-700 Exam Prep

Who Is This For

Built for Engineers Ready to Architect & Build

Azure Data Engineers

Working on Synapse, ADF, or Databricks — add Microsoft Fabric to your production toolkit and stay ahead of the platform shift.

SQL Server / SSIS Devs

Transitioning to cloud-native, lakehouse-first data engineering. Take your SQL skills into the modern Fabric ecosystem.

Data Architects & Leads

Evaluating Microsoft Fabric for enterprise implementation. Get the hands-on validation you need for informed architecture decisions.

Analytics Engineers

Managing dbt or Power BI — understand the full Fabric data stack underneath and own the entire pipeline, not just the analytics layer.

Why MCAL

What Makes This Microsoft Fabric Bootcamp Different

One Continuous Pipeline. Every module adds a real, working layer. By Module 8, you have a complete, production-grade Medallion Lakehouse — not isolated exercises.

Enterprise Gotchas Included. Each module includes real practitioner-level warnings about mistakes that cost enterprises time and money.

DP-700 Certification Track. Dedicated capstone module with exam blueprint walkthrough, mock scenarios, and lab-to-exam mapping.

Live Classroom, Pune. Instructor-led, hands-on, with real-time Q&A and guided labs. No pre-recorded videos. No self-paced isolation.

Enterprise-Grade Depth. V-Order, Liquid Clustering, DirectLake, CU monitoring, RLS/CLS, Purview — topics that separate production engineers from tutorial watchers.

Authority & Trust

Proof, Not Promises

15,000+ professionals from India's top enterprises have trained with MCAL Global since 2010.

IIBA Endorsed

16+ Years

Global Footprint

Enterprise Trusted

Infosys Wipro Accenture TCS IBM ICICI Bank HDFC Bank Barclays Capgemini Deloitte HP Cognizant SBI Credit Suisse Citibank Oracle DBS Bank Persistent Tata Capital Kotak Mahindra BMC Software Syntel Zensar Bajaj Allianz

Market Context

The Demand Is Real. The Talent Gap Is Massive.

$129K

Avg US Salary

₹12-25L

India Mid-Level

<3%

Engineers w/ Fabric

30 hrs

To Close the Gap

Frequently Asked

Questions & Answers

No. The bootcamp starts with Fabric's architecture from the ground up in Module 1. Prior Azure or data engineering experience helps but is not required. The curriculum assumes zero Fabric knowledge and builds comprehensively from fundamentals to production-grade patterns.
The DP-700 (Microsoft Certified: Fabric Data Engineer Associate) is Microsoft's official certification, launched in 2024. Module 8 is dedicated entirely to exam prep with mock scenarios, exam traps, and lab-to-objective mapping. Every lab maps directly to DP-700 skill domains.
Absolutely. The curriculum addresses architectural migration patterns — where Fabric overlaps with Databricks/Delta Lake, where it replaces Synapse workloads, and where choices differ fundamentally. Many students transition from Azure data backgrounds and find patterns immediately applicable.
In India, Fabric Data Engineers at mid-level (3–5 years) command ₹12–25 LPA, with DP-700 certified professionals earning at the higher end. Globally, the average is $129,500/year in the US, with senior architects exceeding $145,000–$165,000/year.
Yes. Each student works in a live Microsoft Fabric environment throughout all labs. You provision your own Fabric workspace in Session 1 and build actual Lakehouses, Pipelines, Notebooks, and security configurations with real datasets.
Instructor-led classroom training is available in Pune (613, Vision Flora, Pimple Saudagar). The same course is also delivered live online, allowing professionals from Mumbai, Bangalore, Hyderabad, Delhi, Chennai, and globally to attend.
Microsoft Learn provides documentation-level content. This bootcamp provides production-context architecture decisions, instructor-guided labs on enterprise datasets, real-time debugging of common failure patterns, DP-700 exam simulation, and capstone project evaluation.
30 hours of structured, hands-on learning. Typical delivery is 8 weekends. Outside classroom hours, expect 3–5 hours weekly for capstone project work. Total per-week commitment: approximately 7–11 hours during the bootcamp.
Yes. MCAL Global offers corporate batch training with customized delivery schedules, cohort-specific case studies, and post-training support. Contact info@mcal.in or call +91 97505 95595 for enterprise pricing and scheduling.

Your Next Step

Build a Production-Grade Pipeline
in 30 Hours

Microsoft Fabric is the present. Engineers building on it now will define enterprise data for the next decade.

30 hours · 8 modules · DP-700 prep · Enterprise capstone · Certification

+91 97505 95595 · info@mcal.in · 613, Vision Flora, Pimple Saudagar, Pune

Take a Look at Our Office

A modern, student-friendly campus designed for focused learning

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