Data Architecture Design Training Course: Build Scalable Big Data Systems

Introduction

Master the art of crafting robust and scalable data systems with our Data Architecture Design Training Course. This program is meticulously designed to equip you with the essential skills to design scalable and efficient Big Data architectures. In today's data-driven world, the ability to create well-structured and optimized data systems is crucial for handling massive datasets and driving business insights. Our data architecture training course provides hands-on experience and expert guidance, empowering you to build future-proof data solutions.

This Big Data architecture training delves into the core concepts of data architecture design, covering topics such as data modeling, data integration, and system scalability. You'll gain expertise in using industry-standard tools and techniques to build scalable and efficient Big Data architectures that meet the demands of modern data environments. Whether you're a data architect, engineer, or analyst, this data architecture design course will empower you to create impactful data solutions.

Target Audience:

• Data Architects
• Data Engineers
• System Architects
• Big Data Developers
• Database Administrators
• Software Developers
• Anyone needing data architecture design skills

Course Objectives:

• Understand the fundamentals of data architecture design.
• Master the principles of designing scalable Big Data architectures.
• Utilize data modeling techniques for efficient data storage and retrieval.
• Implement data integration strategies for seamless data flow.
• Design data pipelines for efficient data processing.
• Optimize data systems for performance and cost-efficiency.
• Implement data security and governance in data architectures.
• Utilize cloud-based data architecture patterns.
• Troubleshoot and debug data architecture issues.
• Integrate various data technologies for a unified data ecosystem.
• Understand how to monitor and maintain data architectures.
• Explore advanced data architecture patterns and techniques.
• Apply real world use cases for data architecture design.

Duration

10 Days

Course content

Module 1: Introduction to Data Architecture Design

• Fundamentals of data architecture design.
• Overview of data architecture patterns and principles.
• Setting up a development environment for data architecture.
• Introduction to data architecture tools and frameworks.
• Best practices for data architecture.

Module 2: Scalable Big Data Architecture Design

• Designing scalable data systems for high-volume data.
• Utilizing distributed computing and storage techniques.
• Implementing data partitioning and sharding.
• Optimizing data systems for performance and scalability.
• Best practices for scalable architecture design.

Module 3: Data Modeling Techniques

• Relational data modeling and normalization.
• NoSQL data modeling for various data types.
• Data warehousing and data lake modeling.
• Utilizing data modeling tools and techniques.
• Best practices for data modeling.

Module 4: Data Integration Strategies

• Implementing ETL (Extract, Transform, Load) processes.
• Utilizing data virtualization and data federation.
• Implementing change data capture (CDC).
• Utilizing message queues and streaming platforms.
• Best practices for data integration.

Module 5: Data Pipeline Design

• Designing data pipelines for efficient data processing.
• Utilizing data pipeline orchestration tools (Airflow, Kubeflow).
• Implementing real-time data pipelines.
• Optimizing data pipelines for performance.
• Best practices for data pipeline design.

Module 6: Performance and Cost Optimization

• Optimizing data systems for performance.
• Utilizing caching and indexing strategies.
• Implementing cost-effective data storage and processing.
• Monitoring and analyzing system performance.
• Best practices for performance and cost optimization.

Module 7: Data Security and Governance

• Implementing data security in data architectures.
• Utilizing authentication and authorization.
• Implementing data encryption and masking.
• Implementing data governance policies and compliance.
• Best practices for data security and governance.

Module 8: Cloud-Based Data Architecture Patterns

• Designing data architectures on cloud platforms (AWS, Azure, GCP).
• Utilizing cloud-based data services and tools.
• Implementing serverless data architectures.
• Best practices for cloud-based data architecture.

Module 9: Troubleshooting and Debugging Data Architecture Issues

• Debugging data architecture issues.
• Analyzing system logs and error messages.
• Utilizing debugging tools and techniques.
• Identifying and resolving performance bottlenecks.
• Best practices for troubleshooting.

Module 10: Integration of Data Technologies

• Integrating various data technologies (databases, data lakes, etc.).
• Utilizing APIs and data connectors.
• Implementing data mesh architectures.
• Building unified data ecosystems.
• Best practices for technology integration.

Module 11: Monitoring and Maintenance

• Monitoring data architecture performance and health.
• Implementing alerting and notifications.
• Utilizing monitoring tools and dashboards.
• Implementing data architecture maintenance strategies.
• Best practices for monitoring and maintenance.

Module 12: Advanced Data Architecture Patterns

• Implementing event-driven data architectures.
• Utilizing microservices for data processing.
• Implementing data streaming architectures.
• Utilizing graph databases and graph processing.
• Advanced techniques for large-scale data architectures.

Module 13: Data Architecture in Cloud Environments

• Deploying data architectures on cloud platforms (AWS, Azure, GCP).
• Utilizing cloud-based data architecture services.
• Optimizing cloud resources for data architectures.
• Best practices for cloud deployment.

Module 14: Data Architecture and Data Governance

• Implementing data governance policies in data architectures.
• Utilizing metadata management tools.
• Implementing data lineage and data dictionary.
• Best practices for data governance.

Module 15: Future Trends in Data Architecture Design

• Emerging trends in data architecture design.
• Utilizing AI and automation in data architectures.
• Implementing data fabric architectures.
• Best practices for future data architecture.

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.