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The Cloudera Data Engineering with Apache Iceberg course is designed for professionals who want to build modern data engineering skills using Cloudera CDP, Apache Iceberg, Spark, Hive, Kafka, and Airflow. The training focuses on creating scalable data pipelines, managing large data lakes, designing lakehouse architectures, and processing both batch and streaming data. Through hands-on projects and real-world scenarios, learners gain practical experience in ETL/ELT development, data governance, performance optimization, and cloud data engineering. This course is ideal for data engineers, Spark developers, ETL professionals, cloud data engineers, data architects, and anyone looking to build expertise in modern enterprise data platforms.
Duration of Training : 40–50 Hours
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Detailed Syllabus • Hands-on Labs • Assignments • Support-Focused • Implementation
Curriculum Designed by Experts
(CDP + Spark + Hive + Apache Iceberg + Kafka + Airflow + Data Governance +
Cloud Data Engineering)
Duration: 40–50 Hours
Projects: 5 Enterprise Projects
Assignments: 12 Hands-On Assignments
Job-Oriented Scenarios: 15 Real-World Industry Scenarios
Outcome: Become a modern Data Engineer capable of building enterprise-scale Lakehouse
platforms using Cloudera CDP and Apache Iceberg.
• Data Engineers
• Big Data Developers
• Hadoop Administrators
• Spark Developers
• ETL Developers
• Cloud Data Engineers
• Database Professionals
• Data Architects
By the end of this training, participants will be able to:
✅ Build Enterprise Data Pipelines using Cloudera CDP
✅ Work with Apache Iceberg Tables
✅ Design Lakehouse Architectures
✅ Implement Data Ingestion Frameworks
✅ Manage Large-Scale Data Lakes
✅ Build ETL/ELT Pipelines using Spark
✅ Perform Data Governance & Metadata Management
✅ Optimize Query Performance
✅ Handle Streaming and Batch Data Processing
Topics
Introduction to Data Engineering
• Data Warehouse Concepts
• Data Lake Concepts
• Lakehouse Architecture
• ETL vs ELT
• Data Engineering Lifecycle
Big Data Fundamentals
• Structured Data
• Semi-Structured Data
• Unstructured Data
Assignment
Design Enterprise Data Architecture.
Job Scenario
Create a modern data platform for a retail company.
Topics
Introduction to CDP
CDP Components
• Data Hub
• Data Warehouse
• Data Engineering
• Data Flow
• Data Catalog
CDP Deployment Models
• Public Cloud
• Private Cloud
• Hybrid Cloud
Security Architecture
Practical Lab
Explore CDP Environment.
Assignment
Build CDP Reference Architecture.
Topics
HDFS Architecture
YARN
Hive
HBase
Sqoop
ZooKeeper
Spark Overview
Lab
Manage Hadoop Environment.
Assignment
Deploy Sample Hadoop Workflow.
Topics
Spark Architecture
RDD
DataFrames
Spark SQL
Transformations
Actions
Spark Optimization
Partitioning
Practical Lab
Develop Spark Applications.
Assignment
Process Large Datasets using Spark.
Job Scenario
Build scalable ETL pipeline.
Topics
Hive Architecture
Hive Metastore
Partitioning
Bucketing
Query Optimization
ACID Tables
Practical Lab
Create Enterprise Data
Warehouse.
Assignment
Design Sales Data
Warehouse.
Topics
Introduction to Iceberg
Why Iceberg?
Iceberg vs Hive Tables
Iceberg vs Delta Lake
Iceberg vs Hudi
Table Formats
Hidden Partitioning
Snapshot Architecture
Time Travel
Schema Evolution
Practical Lab
Create Iceberg Tables.
Assignment
Build Lakehouse Table Structure.
Job Scenario
Migrate Legacy Hive Tables to Iceberg
Topics
Snapshots
Branching
Tagging
Rollbacks
Incremental Reads
Metadata Management
Partition Evolution
Data File Management
Practical Lab
Implement Time Travel Queries.
Assignment
Create Version-Controlled Data Lake.
Topics
Batch Ingestion
Real-Time Ingestion
CDC (Change Data Capture)
Kafka Integration
Database Connectors
API-Based Ingestion
Practical Lab
Ingest Data into Iceberg Tables.
Assignment
Build Data Ingestion Pipeline.
Job Scenario
Load ERP data into Data Lakehouse.
Topics
Data Cleansing
Data Enrichment
Data Validation
Data Standardization
Data Quality Checks
Spark ETL Framework
Practical Lab
Develop ETL Jobs.
Assignment
Build Customer Data Pipeline.
Topics
Data Governance Fundamentals
Metadata Management
Data Catalog
Lineage Tracking
Data Classification
Compliance Management
Cloudera Data Catalog
Apache Atlas
Practical Lab
Implement Data Governance.
Assignment
Create Enterprise Data Catalog.
Job Scenario
Ensure regulatory compliance.
Topics
Authentication
Authorization
Ranger Overview
Role-Based Access Control
Encryption
Auditing
Practical Lab
Configure Data Security Policies.
Assignment
Implement Data Access Controls.
Topics
Apache Airflow
Cloudera Workflows
Scheduling
Dependency Management
Monitoring
Error Handling
Practical Lab
Automate ETL Pipelines.
Assignment
Build Workflow Automation.
Topics
Query Optimization
Spark Optimization
Iceberg Performance Tuning
Partition Strategy
Compaction
Resource Optimization
Practical Lab
Optimize Data Processing Workloads.
Assignment
Improve ETL Performance.
Job Scenario
Reduce ETL processing time by 50%.
Topics
Kafka Fundamentals
Spark Structured Streaming
Real-Time Processing
Event-Driven Architecture
Iceberg Streaming Integration
Practical Lab
Real-Time Data Pipeline.
Assignment
Build Streaming ETL System.
Topics
AWS Integration
Azure Integration
GCP Integration
Object Storage
• Amazon S3
• Azure ADLS
• Google Cloud Storage
Hybrid Data Platforms
Practical Lab
Deploy Lakehouse in Cloud.
Assignment
Design Multi-Cloud Data Architecture.
Topics
Pipeline Monitoring
Data Quality Monitoring
Alerting
Logging
SLA Monitoring
Operational Dashboards
Practical Lab
Build Monitoring Dashboard.
Project 1: Retail Data Lakehouse using Iceberg
Deliverables
• Customer Data Lake
• Sales Data Lakehouse
• Time Travel Reporting
• Governance Framework
Project 2: Banking Data Platform
Deliverables
• Transaction Processing
• CDC Pipelines
• Compliance Reporting
• Metadata Catalog
Project 3: Healthcare Data Lakehouse
Deliverables
• Patient Data Integration
• Data Quality Framework
• Secure Access Controls
Project 4: Real-Time Streaming Analytics Platform
Deliverables
• Kafka Integration
• Spark Streaming
• Iceberg Storage
• Dashboard Reporting
Project 5: Enterprise Data Modernization
Deliverables
• Hive-to-Iceberg Migration
• Performance Optimization
• Governance Implementation
Assignment 1
Design Data Lake Architecture
Assignment 2
Create Spark ETL Pipeline
Assignment 3
Build Hive Data Warehouse
Assignment 4
Implement Iceberg Tables
Assignment 5
Perform Time Travel Queries
Assignment 6
Create CDC Pipeline
Assignment 7
Configure Ranger Security
Assignment 8
Build Metadata Catalog
Assignment 9
Develop Airflow Workflows
Assignment 10
Optimize Iceberg Performance
Assignment 11
Implement Streaming Pipeline
Assignment 12
Deploy Cloud Data Platform
Scenario 1
Migrate Hive Data Warehouse to Apache Iceberg.
Scenario 2
Build Lakehouse architecture for banking data.
Scenario 3
Implement CDC from Oracle to Iceberg.
Scenario 4
Create time-travel reporting solution.
Scenario 5
Design secure healthcare data platform.
Scenario 6
Implement enterprise data governance.
Scenario 7
Optimize Spark jobs processing 10TB+ data.
Scenario 8
Build Kafka real-time analytics platform.
Scenario 9
Manage schema evolution without downtime.
Scenario 10
Reduce cloud storage costs through Iceberg optimization.
Scenario 11
Build enterprise metadata management solution.
Scenario 12
Implement regulatory compliance controls.
Scenario 13
Handle large-scale partition evolution.
Scenario 14
Perform disaster recovery for data platform.
Scenario 15
Deploy hybrid cloud data lakehouse.
Cloudera Platform
• Cloudera CDP
• Cloudera Data Engineering
• Cloudera Data Warehouse
• Cloudera Data Catalog
Big Data
• Hadoop
• HDFS
• Hive
• Spark
Lakehouse
• Apache Iceberg
• Hive Tables
• Parquet
• ORC
Streaming
• Apache Kafka
• Spark Structured Streaming
Governance
• Apache Atlas
• Ranger
Workflow
• Apache Airflow
Cloud
• AWS S3
• Azure Data Lake Storage
• Google Cloud Storage
• Cloudera Data Engineer
• Big Data Engineer
• Apache Spark Developer
• Lakehouse Engineer
• Data Platform Engineer
• Hadoop Developer
• Cloud Data Engineer
• ETL Developer
• Data Architect
• Analytics Engineer
Cloudera Certifications
• Cloudera Data Platform (CDP)
• Cloudera Data Engineer Certification
• Cloudera Administrator Certification
Complementary Certifications
• Apache Spark Certification
• AWS Data Engineer Associate
• Microsoft Azure Data Engineer (DP-203)
• Databricks Data Engineer Associate
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