Delta Lake and Data Versioning is a cutting-edge training course designed to empower data professionals with the knowledge and practical skills to implement transactional storage layers on top of existing data lakes. Built on open-source technologies and tightly integrated with Apache Spark, Delta Lake addresses the critical challenges of data reliability, consistency, and scalability in big data environments. This course explores key features such as ACID transactions, schema enforcement, time travel, and data versioning—enabling organizations to build robust, production-grade data pipelines. Participants will learn how to unify batch and streaming workloads, manage metadata efficiently, and implement auditing, rollback, and lineage capabilities critical for regulatory compliance and enterprise data governance.

Duration: 10 Days

Target Audience

• Data Engineers
• Big Data Architects
• Cloud Data Platform Developers
• Data Lake Administrators
• DataOps Engineers
• Business Intelligence Developers
• Data Governance Professionals
• Analytics Engineers

Course Objectives

• Understand the architecture and core concepts of Delta Lake
• Explore ACID transactions and their role in reliable data lakes
• Implement data versioning and time travel for auditing and rollback
• Learn schema enforcement and evolution techniques
• Manage large-scale data pipelines using Delta Lake and Apache Spark
• Apply Delta Lake to batch and streaming workloads seamlessly
• Enable data quality, integrity, and reliability across data pipelines
• Monitor and optimize performance of Delta Lake tables
• Integrate Delta Lake with cloud-native data services and tools
• Leverage Delta Lake for real-time analytics and machine learning workflows
• Implement compliance-ready versioned data pipelines

Module 1: Introduction to Delta Lake and Data Lake Challenges

• Understanding the limitations of traditional data lakes
• Key features of Delta Lake and its advantages
• Comparison of Parquet, Delta, and other formats
• Overview of open-source Delta Lake architecture
• Use cases for versioned, reliable data lakes

Module 2: Delta Lake Architecture and Storage Layer

• Delta Lake components: transaction log, metadata, data files
• Internals of the Delta log and checkpointing
• How Delta Lake maintains consistency in distributed systems
• File formats and directory structures
• Integration with cloud storage (S3, ADLS, GCS)

Module 3: ACID Transactions in Delta Lake

• Role of ACID properties in big data workloads
• Write operations and multi-writer support
• Commit protocol and transaction handling
• Conflict detection and resolution
• Read consistency and isolation levels

Module 4: Schema Enforcement and Evolution

• Enforcing schemas at write time
• Preventing data corruption through column-level checks
• Managing schema changes over time
• AutoMerge and column mapping
• Best practices for schema compatibility

Module 5: Time Travel and Data Versioning

• Enabling and accessing historical versions of data
• Using VERSION AS OF and TIMESTAMP AS OF queries
• Auditing and rollback of data changes
• Comparing snapshots and diffing datasets
• Managing storage cost for time travel

Module 6: Unified Batch and Streaming with Delta Lake

• Delta as a sink and source for streaming jobs
• Writing streaming data to Delta tables
• Reading Delta tables in structured streaming
• Micro-batch vs. continuous processing
• Handling late-arriving data and watermarking

Module 7: Optimizing Delta Lake Performance

• File size optimization and compaction
• Z-ordering and data skipping
• Auto optimize and auto compaction
• Vacuuming stale data files
• Indexing strategies for faster queries

Module 8: Data Lineage and Audit Trails

• Tracking changes across Delta operations
• Capturing metadata changes
• Integration with data catalogs and governance tools
• Using Delta logs for auditing
• Visualization of lineage with Spark UI

Module 9: Delta Table Operations and Commands

• Creating and managing Delta tables
• MERGE, UPDATE, DELETE, and UPSERT operations
• Partitioning strategies for Delta tables
• DML command optimizations
• Altering and renaming Delta tables

Module 10: Integration with Apache Spark

• Using Delta Lake APIs with PySpark, Scala, and SQL
• SparkSession and Delta-specific options
• Caching and checkpointing with Delta
• Delta operations in Spark notebooks
• Debugging and logging Delta jobs

Module 11: Delta Lake on Databricks and Open Source Platforms

• Running Delta Lake on Databricks
• Delta Lake OSS with Apache Spark
• Differences between open-source and managed Delta
• Compatibility with MLflow and Koalas
• Deployment scenarios and limitations

Module 12: Cloud and Data Platform Integration

• Integrating Delta Lake with Azure Synapse, AWS Glue, and GCP BigLake
• Delta Sharing protocol for secure data exchange
• Connecting Delta Lake to Power BI, Tableau, and Looker
• Storage cost and performance optimization in the cloud
• Managing access control and permissions

Module 13: Data Governance and Compliance Use Cases

• Data retention and deletion policies
• GDPR, HIPAA, and regulatory use cases
• Role of Delta in auditability and traceability
• Implementing secure time travel and rollback
• Data access control at the row and column level

Module 14: Real-Time Analytics with Delta Lake

• Architecture for real-time reporting pipelines
• Use of Delta Lake for operational dashboards
• Materialized views and streaming aggregations
• Integrating Delta with BI tools in near real time
• Caching Delta data for rapid access

Module 15: Project and Best Practices Implementation

• Designing a versioned data lake strategy
• Migrating from legacy data lakes to Delta Lake
• Building production-grade Delta pipelines
• Performance tuning and governance checklist
• Capstone project: build a time-travel-enabled data lake

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.