Data Warehousing & Data Lake Design Training Course: Efficient Data Storage

Introduction

Optimize your data infrastructure with our Data Warehousing and Data Lake Design Training Course. This program is designed to equip you with the essential skills to architect efficient data storage solutions for analytics, enabling you to build robust and scalable data platforms. In today's data-driven world, mastering data warehousing and data lake design is crucial for organizations seeking to derive actionable insights from their data. Our data warehousing training course offers hands-on experience and expert guidance, empowering you to create data storage solutions that support advanced analytics and business intelligence.

This efficient data storage training delves into the core concepts of data warehousing and data lake design, covering topics such as schema design, data modeling, and data integration. You'll gain expertise in using industry-standard techniques to architect efficient data storage solutions for analytics, meeting the demands of modern data-driven organizations. Whether you're a data architect, data engineer, or database administrator, this Data Warehousing & Data Lake Design course will empower you to build and maintain high-performance data storage systems.

Target Audience:

• Data Architects
• Data Engineers
• Database Administrators
• Business Intelligence Developers
• Data Analysts
• System Architects
• Anyone needing data warehousing and data lake design skills

Course Objectives:

• Understand the fundamentals of data warehousing and data lake design.
• Master dimensional modeling and schema design for data warehouses.
• Utilize data lake architectures for flexible data storage and processing.
• Implement ETL/ELT processes for data integration and transformation.
• Design and build efficient data storage solutions for analytics.
• Optimize data storage for performance, scalability, and cost-effectiveness.
• Troubleshoot and address common challenges in data warehousing and data lake design.
• Implement data governance and data quality management in data storage.
• Integrate data warehousing and data lakes with real-world analytics platforms.
• Understand how to handle large datasets and distributed storage.
• Explore advanced data storage techniques (e.g., data virtualization, data mesh).
• Apply real world use cases for data warehousing and data lake design.
• Leverage data storage tools and frameworks for efficient implementation.

Duration

10 Days

Course content

Module 1: Introduction to Data Warehousing and Data Lake Design

• Fundamentals of data warehousing and data lake design.
• Overview of dimensional modeling, data lake architectures, and ETL processes.
• Setting up a data storage design environment.
• Introduction to data storage tools and frameworks.
• Best practices for data storage design.

Module 2: Dimensional Modeling and Schema Design

• Mastering dimensional modeling and schema design for data warehouses.
• Utilizing star schema and snowflake schema design.
• Designing and building fact and dimension tables.
• Optimizing schema design for query performance.
• Best practices for dimensional modeling.

Module 3: Data Lake Architectures

• Utilizing data lake architectures for flexible data storage and processing.
• Implementing data lake design patterns (e.g., bronze, silver, gold layers).
• Designing and building data lake storage solutions.
• Optimizing data lake architectures for scalability.
• Best practices for data lake architectures.

Module 4: ETL/ELT Processes

• Implementing ETL/ELT processes for data integration and transformation.
• Utilizing data integration tools and techniques.
• Designing and building data pipelines for data warehousing and data lakes.
• Optimizing ETL/ELT processes for data quality.
• Best practices for ETL/ELT.

Module 5: Efficient Data Storage Solutions

• Designing and building efficient data storage solutions for analytics.
• Utilizing data storage technologies (e.g., cloud storage, data warehousing appliances).
• Implementing data partitioning and indexing strategies.
• Optimizing data storage for specific analytics workloads.
• Best practices for data storage solutions.

Module 6: Performance and Scalability Optimization

• Optimizing data storage for performance, scalability, and cost-effectiveness.
• Utilizing performance tuning and monitoring tools.
• Implementing data compression and storage optimization techniques.
• Designing scalable data storage architectures.
• Best practices for optimization.

Module 7: Troubleshooting Data Storage Challenges

• Debugging common challenges in data warehousing and data lake design.
• Analyzing data storage performance and errors.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common data storage issues.
• Best practices for troubleshooting.

Module 8: Data Governance and Quality Management

• Implementing data governance and data quality management in data storage.
• Utilizing data quality checks and validation techniques.
• Designing and building data governance policies.
• Optimizing data storage for data integrity.
• Best practices for governance.

Module 9: Integration with Analytics Platforms

• Integrating data warehousing and data lakes with real-world analytics platforms.
• Utilizing BI tools and data visualization platforms.
• Implementing data access and security measures.
• Optimizing integration for data-driven insights.
• Best practices for integration.

Module 10: Large Datasets and Distributed Storage

• Understanding how to handle large datasets and distributed storage.
• Utilizing distributed storage systems (e.g., Hadoop, Spark).
• Implementing data partitioning and parallel processing.
• Designing scalable data storage solutions for big data.
• Best practices for large datasets.

Module 11: Advanced Data Storage Techniques

• Exploring advanced data storage techniques (data virtualization, data mesh).
• Utilizing data virtualization for data integration.
• Implementing data mesh architectures for decentralized data ownership.
• Designing and building advanced data storage solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced techniques.

Module 12: Real-World Use Cases

• Implementing data warehousing for business intelligence and reporting.
• Utilizing data lakes for data science and machine learning.
• Implementing data storage solutions for real-time analytics.
• Utilizing data storage for customer data platforms.
• Best practices for real-world applications.

Module 13: Data Storage Tools and Frameworks Implementation

• Utilizing data storage tools and frameworks (Snowflake, Databricks, AWS Redshift).
• Implementing data storage solutions with specific tools.
• Designing and building data storage pipelines.
• Optimizing tool usage for efficient implementation.
• Best practices for tool implementation.

Module 14: Data Storage Performance Monitoring

• Implementing data storage performance monitoring.
• Utilizing data storage metrics and monitoring tools.
• Designing and building performance dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 15: Future Trends in Data Storage Design

• Emerging trends in data storage design.
• Utilizing AI for data storage optimization.
• Implementing data storage in cloud-native environments.
• Best practices for future applications.

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.