Enterprise Data Integration and Federation is a critical training course designed to equip data professionals with the skills to unify, standardize, and deliver distributed data across an organization. As modern enterprises operate across hybrid, multi-cloud, and on-prem environments, data is often siloed across disparate sources. This course provides in-depth expertise on integrating structured, semi-structured, and unstructured data from multiple systems into a unified view, using modern data federation techniques. Participants will explore ETL/ELT architectures, data virtualization, metadata management, and API-driven data services, empowering them to create scalable, secure, and governed data environments that enable real-time insights and drive enterprise-wide analytics and decision-making.

Duration: 10 Days

Target Audience

• Enterprise Data Architects
• Data Integration Engineers
• Data Platform Managers
• Cloud Data Engineers
• Analytics and BI Developers
• Solution Architects
• Data Governance Professionals
• IT Professionals overseeing data systems

Course Objectives

• Understand the core principles and challenges of enterprise data integration
• Explore various data federation architectures and when to use them
• Design scalable ETL and ELT pipelines for batch and real-time data movement
• Use data virtualization tools for unified access to distributed datasets
• Integrate cloud and on-premise data seamlessly
• Apply security, governance, and compliance policies across federated environments
• Implement metadata management to drive data discoverability
• Monitor and optimize data integration workflows
• Create API-based data services for flexible data access
• Enable business intelligence platforms through real-time data federation
• Develop strategic roadmaps for enterprise-wide data unification initiatives

Module 1: Fundamentals of Enterprise Data Integration

• Overview of data integration goals and business impact
• Types of data integration (ETL, ELT, replication, federation)
• Data latency considerations: batch, micro-batch, streaming
• Integration tools and technologies overview
• Common challenges in large-scale data integration

Module 2: Architectures for Data Federation

• Centralized vs. decentralized integration approaches
• Federated data access models and hybrid patterns
• Query federation across heterogeneous systems
• Role of metadata in data federation
• Comparison of key data federation platforms

Module 3: Designing Scalable ETL Pipelines

• ETL vs. ELT architectures in modern data stacks
• Extract strategies: API-based, change data capture, file-based
• Data transformation frameworks and tools
• Loading strategies for relational and non-relational targets
• Handling schema evolution and data type conversions

Module 4: Data Virtualization Techniques

• Understanding data virtualization concepts
• Tools: Denodo, Dremio, SAP HANA, etc.
• Query pushdown and performance optimization
• Virtual views vs. materialized views
• Governing access in virtualized environments

Module 5: Integration with Cloud and On-Premise Systems

• Hybrid data pipeline design considerations
• Connecting to legacy systems and mainframes
• Securing cloud data transfers
• Latency and consistency across environments
• Tool support for hybrid data integration

Module 6: API-Based Data Integration

• Designing RESTful and GraphQL APIs for data access
• Data-as-a-service (DaaS) models
• API gateways and throttling
• JSON, XML, and protocol support
• Integrating APIs with ETL and orchestration tools

Module 7: Metadata Management and Data Catalogs

• Role of metadata in integration and federation
• Building enterprise data catalogs
• Automated metadata extraction
• Lineage tracking and data profiling
• Enhancing data discovery and compliance

Module 8: Data Quality and Transformation Standards

• Ensuring data quality during integration
• Data cleansing and enrichment techniques
• Standardizing formats, units, and naming conventions
• Validation rules and error handling
• Monitoring and auditing transformation pipelines

Module 9: Real-Time and Streaming Data Integration

• Event-based architecture principles
• Ingestion tools: Kafka, Flink, Kinesis, etc.
• Stream processing frameworks
• Capturing change data using CDC
• Combining real-time and batch pipelines

Module 10: Governance, Security, and Compliance

• Access control and data masking strategies
• Policy enforcement for federated data
• Compliance with GDPR, HIPAA, CCPA, etc.
• Role-based and attribute-based access models
• Audit trails and activity logging

Module 11: Orchestration and Workflow Automation

• Scheduling and dependency management
• Tools: Apache Airflow, Prefect, Control-M
• Handling retries, failures, and alerts
• Parameterization and environment variables
• Building end-to-end workflow DAGs

Module 12: Performance Optimization and Monitoring

• Tuning ETL and ELT for large data volumes
• Load balancing and parallel processing
• Query optimization for federated sources
• Metrics, logging, and dashboards
• Proactive bottleneck identification

Module 13: Data Integration for Business Intelligence

• Enabling analytics with consistent datasets
• Connecting integrated data to BI tools
• Semantic modeling and data cubes
• Aggregation logic and derived metrics
• Supporting ad-hoc queries and dashboards

Module 14: Case Studies in Enterprise Integration

• Financial data integration across business units
• Healthcare system data federation use case
• Telecom real-time streaming pipeline example
• Manufacturing IoT data consolidation
• Government open data federation

Module 15: Capstone and Strategic Roadmap Planning

• Designing a full-stack enterprise integration architecture
• Aligning integration strategy with business goals
• Creating data source inventories and mapping flows
• Roadmap for integration modernization
• Presentation and peer feedback

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.