Kiram A.
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Online Course
new
free
Introduction to Data Warehousing
with
Rahul Singh
Unlock the power of data with our comprehensive Data Warehousing course. Learn to design, build, and optimize enterprise-grade data warehouses using real-world case studies, advanced ETL/ELT techniques, real-time analytics, and automation.
591 students already have enrolled
Skill level:
Basic
Duration:
3 hours
-
Lessons (3 hours)
- Lessons (3 hours)
CPE credits:
4
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
Accredited:
certificate
What You Learn
- Understand data warehousing concepts, history, and architecture.
- Design and implement dimensional models with fact and dimension tables.
- Develop robust ETL/ELT pipelines for batch and real-time data.
- Optimize performance with indexing, partitioning, and materialized views.
- Integrate BI tools for dynamic reporting and visualizations.
Topics & tools
data warehousedata transformationdata preprocessingdata engineeringdashboard reportingdata literacytheory
Your instructor
Product Manager | Data Systems at Bloomberg | AI & Cloud Expert
Track record
Bringing real-world expertise from leading global companies
Academic background
Master's degree, Data Science
Course OVERVIEW
Description
CPE Credits: 4
Field of Study: Information Technology
Delivery Method: QAS Self Study
Delivery Method: QAS Self Study
This Data Warehousing course provides a deep dive into designing, building, and managing robust data warehouse solutions. Throughout the course, you'll explore fundamental concepts and advanced techniques that are essential for any data professional.
The curriculum covers:
- Introduction & History: Understand the evolution of data warehousing and its role in modern data ecosystems.
- Core Components: Learn about data warehouse architecture, including source, staging, and presentation layers, ETL/ELT processes, and querying.
- Dimensional Modeling & Schema Design: Master star schemas, snowflake schemas, Slowly Changing Dimensions (SCDs), and advanced schema techniques to capture business history effectively.
- Performance Optimization: Discover strategies like indexing, partitioning, and materialized views to enhance query performance.
- Real-Time & Cloud Solutions: Compare traditional on-premises systems with cloud-native and hybrid architectures, and explore real-time data processing techniques.
- Data Visualization & Reporting: Connect your warehouse to BI tools like Tableau and Power BI to create interactive dashboards and reports.
- Case Study Project: Apply your learning in a comprehensive capstone project using FashionFusion, a real-world scenario that requires both batch and real-time processing for structured and unstructured data.
By the end of this course, you’ll be equipped with practical, hands-on skills to build and manage scalable data warehouses, making you ready to tackle real-world data challenges in any industry.
Prerequisites
- Basic understanding of data concepts (such as databases, tables, and files) is helpful but not required.
Advanced preparation
Curriculum
31 lessons
31 exercises
1 exam
- 2. Data Warehousing Basics20 Min
Learn the fundamentals of data warehousing, including definitions, evolution, and core components. Discover the business value, benefits, and real-world applications of data warehouses.
- 3. Data Warehousing Architecture and Design32 Min
Explore scalable data warehouse design with traditional versus modern architectures, dimensional modeling, schema design, partitioning, and performance optimization techniques.
- 4. Implementation and Management16 Min
Focus on the full development lifecycle from requirements gathering and design to deployment, maintenance, data quality, governance, and security for robust data systems.
- 5. ETL Processes and Data Integration28 Min
Understand ETL/ELT processes and data integration techniques. This chapter covers extraction, transformation, loading strategies, and automation for handling both batch and real-time data.
- 6. Data Warehousing Tools and Technologies22 Min
Review popular data warehousing platforms and tools, including Snowflake, Redshift, BigQuery, and Synapse. Learn SQL querying, cloud vs. on-premises solutions, and best practices for visualization and reporting.
- 7. Advanced Data Warehousing Concepts27 Min
Dive into advanced topics such as data lakehouses, real-time data warehousing, advanced schema designs including SCDs and bridge tables, and techniques for managing large volumes of data.
- 8. Capstone: Build a Complete Data Warehouse19 Min
Apply all course concepts in a comprehensive case study. Design, implement, and monitor a complete data warehouse solution that integrates batch and real-time processing for real-world scenarios.
- 9. Course exam30 Min
Free preview
1.1 Introduction to the Course
4 min
2.1 Foundations of Data Warehousing
4 min
2.2 History and Evolution
5 min
2.4 Core Components of a Data Warehouse
6 min
2.5 Real-World Applications
5 min
9 in 10
of our graduates landed a new AI & data job
after enrollment
96%
of our students recommend
365 Data Science.
94%
of AI and data science graduates
successfully change
or advance their careers.
ACCREDITED certificates
Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global
institutions.
Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities
employers value most.
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