Online Course new
Introduction to Data Warehousing

Name: Introduction to Data Warehousing Course
Price: 36 USD

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.

4.8

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1,040 students already enrolled

Skill level:

Basic

Duration:

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

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

Rahul Singh

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

Ask Rahul a question

Course overview

Accredited certificates

Course OVERVIEW

Description

CPE Credits: 4 Field of Study: Information Technology
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

Intro to Data Engineering

Curriculum

31 lessons 31 exercises 1 exam

1. Introduction to Data Warehousing

4 min

This chapter introduces the instructor and provides an overview of the course. It outlines the journey into data warehousing, setting the stage with key concepts and real-world case studies.

4 min

This chapter introduces the instructor and provides an overview of the course. It outlines the journey into data warehousing, setting the stage with key concepts and real-world case studies.

Introduction to the Course Free
2. Data Warehousing Basics

20 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.

20 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.

Foundations of Data Warehousing Free

History and Evolution Free

Exercise Free

Core Components of a Data Warehouse Free

Real-World Applications Free

Exercise Free
3. Data Warehousing Architecture and Design

32 min

Explore scalable data warehouse design with traditional versus modern architectures, dimensional modeling, schema design, partitioning, and performance optimization techniques.

32 min

Explore scalable data warehouse design with traditional versus modern architectures, dimensional modeling, schema design, partitioning, and performance optimization techniques.

Traditional vs. Modern Warehouse Architectures

Dimensional Modeling

Exercise

Schema Design Principles

Understanding Data Partitioning

Exercise

Indexing Databases

Performance Optimization in Querying

Exercise
4. Implementation and Management

16 min

Focus on the full development lifecycle from requirements gathering and design to deployment, maintenance, data quality, governance, and security for robust data systems.

16 min

Focus on the full development lifecycle from requirements gathering and design to deployment, maintenance, data quality, governance, and security for robust data systems.

Data Warehouse Development Lifecycle

Exercise

Data Quality and Governance

Data Security and Privacy

Exercise
5. ETL Processes and Data Integration

28 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.

28 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.

Introduction to Data Integration

Data Extraction

Exercise

Data Transformation Concepts

Exercise

Strategies for Data Loading

Automation in Data Warehouses

Exercise
6. Data Warehousing Tools and Technologies

22 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.

22 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.

Overview of Data Warehousing Technologies

Querying Data in a Warehouse

Exercise

Cloud vs. On-Premises Data Warehousing

Data Visualization and Reporting

Exercise
7. Advanced Data Warehousing Concepts

27 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.

27 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.

Data Warehouse vs. Data Lakehouse

Real-Time Data Warehousing

Exercise

Slowly Changing Dimensions

Advanced Schema Designs

Managing Large Volumes of Data

Exercise
8. Capstone: Build a Complete Data Warehouse

19 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.

19 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.

Requirements Gathering and System Design

Designing Data Warehouse Architecture

Implementing and Monitoring the System

Exercise
9. Course exam

30 min

30 min

Course exam

Free lessons

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

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Platform worth of time! Perfect visualization, simple language, quality curriculum.

Kiram A.

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In 2023, I decided to rewrite my story—leaving accounting to become a freelance Data and Business Analyst. At first, I was completely lost, until a friend recommended 365 Data Science. The structured learning paths, real-world projects, and clear explanations transformed my skills and confidence. Within six months, I mastered Python, built interactive dashboards, and landed five clients across four countries. 365 didn’t just teach me—it reshaped my career and sparked my curiosity for AI.