AZURE SYNAPSE ANALYTICS – BASIC TO ADVANCED

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The Azure Synapse Analytics – Basic to Advanced syllabus covers end-to-end analytics on Microsoft Azure, including data warehousing, big data processing, SQL pools, Spark, data integration, and performance optimization. It explains how Synapse unifies data engineering, analytics, and reporting on a single platform. This syllabus is important because it enables organizations to analyze large-scale data efficiently and make data-driven decisions in real time. It is best suited for data engineers, BI professionals, analytics engineers, cloud professionals, and graduates aiming to build a career in modern data analytics on Azure.

Duration of Training : 50 Hours
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Detailed Syllabus • Hands-on Labs • Assignments • Projects
Target Roles : Senior Data Engineer | Analytics Engineer | BI Engineer | Cloud Data Architect

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Overview

The Syllabus

Curriculum Designed by Experts

Prerequisites

✔ SQL fundamentals
✔ Data Warehouse & ETL concepts
✔ Basic Azure knowledge

OPTION A: 50-HOUR ADVANCED SYLLABUS

Area	Hours
Core Synapse & Architecture	30
Advanced Analytics & Integration	10
Enterprise Projects	6
Assignments & Interview Scenarios	4
Total	50 Hours

MODULE 1: Modern Data & Analytics Architecture (3 Hours)

Evolution of analytics platforms
OLTP vs OLAP vs HTAP
Data Warehouse vs Data Lake vs Lakehouse
Enterprise analytics reference architectures
Azure analytics ecosystem deep dive
Lab
Azure subscription & environment setup

MODULE 2: Azure Synapse Architecture – Deep Dive (5 Hours)

Synapse Analytics overview
Workspace architecture
Synapse Studio components
Serverless SQL Pool – use cases
Dedicated SQL Pool – enterprise workloads
Apache Spark pools
Data Explorer (overview)
Cost & scalability planning
Lab
Create and configure Synapse workspace
Link storage & compute

MODULE 3: Azure Data Lake Gen2 – Enterprise Governance (5 Hours)

Enterprise Data Lake design principles
Bronze / Silver / Gold zones
File format strategy
Partitioning & folder standards
Security model (RBAC & ACL)
Data lifecycle & retention
Naming, tagging & governance
Lab
Design enterprise-grade Data Lake structure

MODULE 4: Synapse SQL Pools – Enterprise Usage (6 Hours)

Serverless SQL Pool
Ad-hoc analytics use cases
Schema-on-read concepts
Cost-eeicient analytics

Dedicated SQL Pool
MPP architecture
Data distribution strategies
Indexing concepts
Data loading strategies
Workload management
Performance monitoring & tuning concepts

Lab
Design enterprise data warehouse schema

MODULE 5: Apache Spark in Synapse – Advanced Concepts (6 Hours)

Spark architecture in Synapse
Spark pool configuration
Spark vs SQL decision matrix
Large-scale data processing lifecycle
Delta Lake architecture
Incremental processing concepts
Performance & scalability planning
Lab
Design Spark-based transformation workflows

MODULE 6: Synapse Pipelines – Enterprise ETL/ELT (4 Hours)

Synapse Pipelines architecture
Comparison with Azure Data Factory
Linked services & datasets
Parameterization strategy
Scheduling & orchestration
Error handling & retries
CI/CD concepts for pipelines
Lab
Build end-to-end data integration workflow

MODULE 7: Security, Monitoring & Cost Optimization (4 Hours)

Workspace-level security
SQL & Spark access control
Data masking & encryption concepts
Monitoring with Azure Monitor
Cost control & optimization strategies
Capacity planning
Lab
Secure and monitor Synapse workloads

MODULE 8: Power BI & Downstream Integration (3 Hours)

Power BI integration patterns
Import vs DirectQuery
Semantic model design
Performance optimization concepts
Sharing & governance
Lab
Create enterprise BI reporting workflow

MODULE 9: Enterprise Projects (6 Hours)

Project 1: Enterprise Data Warehouse on Azure Synapse
End-to-end analytics architecture
Data Lake + DW implementation
Analytics & reporting enablement

Project 2: Big Data Analytics Platform
Large-scale data processing design Cost-optimized analytics using Synapse

MODULE 10: Assignments & Interview Scenarios (4 Hours)

Architecture design assignments
Performance troubleshooting scenarios
Cost optimization case studies
Production issue handling
Real MNC interview questions

OPTION B: 60-HOUR MASTER / ARCHITECT-LEVEL SYLLABUS

Area	Hours
Core & Advanced Synapse	34
Advanced Integrations & Real-Time Analytics	10
Enterprise Projects	10
Interview, Architecture & Case Studies	6
Total	60 Hours

ADDITIONAL MODULES (Beyond 50 Hours)

MODULE 11: Near Real-Time & Streaming Analytics (4 Hours)

Batch vs streaming analytics
Event-driven analytics architecture
Integration with Event Hubs
Near real-time reporting use cases

MODULE 12: Advanced Integrations (4 Hours)

Synapse with Azure Databricks
Synapse with Azure Machine Learning
Data science integration scenarios
AI-driven analytics overview

MODULE 13: CI/CD & DevOps for Synapse (3 Hours)

Source control integration
Environment promotion (Dev → Test → Prod)
Release management concepts
Infrastructure-as-Code overview

MODULE 14: Enterprise-Scale Projects (10 Hours)

Capstone Project: Enterprise Analytics Platform
Multi-source data ingestion
Data Lake governance
Hybrid SQL + Spark architecture
Secure analytics environment
BI & advanced analytics integration

Deliverables
Architecture diagrams
Design documents
Project walkthrough (resume-ready)

MODULE 15: Architect-Level Scenarios & Interview Prep (6 Hours)

Synapse vs Databricks vs Fabric
Handling petabyte-scale data
Cost explosion troubleshooting
Security breach response
Migration from on-prem DW to Azure
Senior-level interview case studies

🎯 FINAL LEARNING OUTCOME (50 / 60 Hours)

After completing this program, learners can:
✅ Design enterprise analytics architectures
✅ Implement and govern Azure Synapse platforms
✅ Handle large-scale production workloads
✅ Optimize performance, security & cost
✅ Clear senior-level interviews confidently

🏆 CERTIFICATION ALIGNMENT

DP-203 – Azure Data Engineer Associate
PL-300 – Power BI Data Analyst
AZ-305 – Azure Solutions Architect (Analytics exposure)

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Azure Synapse Analytics Course Certification With Training In Bangalore

Q: OPTION A: 50-HOUR ADVANCED SYLLABUS

Area Hours Core Synapse & Architecture 30 Advanced Analytics & Integration 10 Enterprise Projects 6 Assignments & Interview Scenarios 4 Total 50 Hours

Q: MODULE 4: Synapse SQL Pools – Enterprise Usage (6 Hours)

Serverless SQL Pool Ad-hoc analytics use cases Schema-on-read concepts Cost-eeicient analytics Dedicated SQL Pool MPP architecture Data distribution strategies Indexing concepts Data loading strategies Workload management Performance monitoring & tuning concepts Lab Design enterprise data warehouse schema

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