Databricks Lakehouse Certification

Module 1: Introduction to Databricks Lakehouse

• Lakehouse Fundamentals
• Databricks Platform Overview
• Modern Data Architecture
• Lakehouse Benefits
• Industry Applications

Module 2: Databricks Workspace

• Workspace Navigation
• Clusters
• Notebooks
• Workspace Management
• Collaboration Features

Module 3: Apache Spark on Databricks

• Spark Architecture
• Spark Sessions
• DataFrames
• Spark SQL
• Distributed Processing

Module 4: Delta Lake Fundamentals

• Delta Lake Architecture
• ACID Transactions
• Schema Enforcement
• Time Travel
• Data Versioning

Module 5: Data Ingestion

• Batch Data Ingestion
• Streaming Data Ingestion
• File-Based Sources
• Database Integration
• Data Import Best Practices

Module 6: ETL Pipeline Development

• Data Extraction
• Data Transformation
• Data Loading
• Workflow Design
• Pipeline Automation

Module 7: Data Transformation

• Data Cleaning
• Data Validation
• Data Aggregation
• Joins
• Business Logic Implementation

Module 8: Databricks SQL

• SQL Warehouses
• Query Development
• Views
• Performance Optimization
• Analytics Queries

Module 9: Workflow Orchestration

• Job Scheduling
• Workflow Dependencies
• Task Automation
• Pipeline Monitoring
• Error Handling

Module 10: Delta Live Tables

• Pipeline Development
• Data Quality Rules
• Incremental Processing
• Monitoring Pipelines
• Pipeline Optimization

Module 11: Data Governance

• Unity Catalog Concepts
• Metadata Management
• Data Lineage
• Data Discovery
• Governance Best Practices

Module 12: Security and Access Management

• Authentication
• Authorization
• Role-Based Access Control
• Data Encryption
• Security Best Practices

Module 13: Performance Optimization

• Query Optimization
• Cluster Optimization
• Caching
• Partitioning
• Resource Management

Module 14: Machine Learning Integration

• Machine Learning Workflows
• Feature Engineering
• Model Training
• Model Tracking
• Model Deployment Concepts

Module 15: Real-Time Data Processing

• Structured Streaming
• Stream Processing
• Event Processing
• Streaming Pipelines
• Monitoring Streaming Jobs

Module 16: Cloud Integration

• Cloud Storage Integration
• Managed Services
• Multi-Cloud Deployment
• Data Migration
• Cloud Best Practices

Module 17: Monitoring and Troubleshooting

• Cluster Monitoring
• Job Monitoring
• Log Analysis
• Error Diagnosis
• Performance Monitoring

Module 18: DevOps for Databricks

• Version Control
• CI/CD Concepts
• Repository Management
• Automated Deployment
• Release Management

Module 19: Enterprise Data Engineering

• Scalable Data Pipelines
• Enterprise Architecture
• Data Lakehouse Design
• Operational Excellence
• Production Readiness

Module 20: Integration with Data Ecosystem

• Apache Kafka Integration
• Data Warehouse Integration
• Business Intelligence Integration
• API Integration
• External Data Sources

Module 21: Best Practices

• Coding Standards
• Documentation
• Cost Optimization
• Operational Best Practices
• Continuous Improvement

Module 22: Advanced Lakehouse Features

• Data Sharing
• Data Marketplace Concepts
• Lakehouse Optimization
• Advanced Analytics
• Platform Administration

Module 23: Production Deployment

• Deployment Strategies
• Monitoring Production Pipelines
• Backup and Recovery
• Disaster Recovery Planning
• Operational Maintenance

Module 24: Databricks Lakehouse Project

• End-to-End Data Pipeline Development
• Delta Lake Implementation
• Data Engineering Workflow
• Performance Optimization
• Final Project Presentation