This comprehensive course provides an introduction to the fundamental concepts of data warehousing. Through the use of industry examples and real-world datasets, participants will develop a strong understanding of the basics of data warehousing. The global data warehousing market is projected to exceed $50 billion by 2028, making this an opportune time to gain knowledge in this field. The course begins by examining the definition and purpose of a data warehouse, as well as its distinctions from data lakes and data mart systems. Participants will explore how various data professionals, including data engineers, data scientists, and analysts, interact with a data warehouse throughout its lifecycle, from development to production and ongoing maintenance. Once the foundational knowledge is established, participants will delve into the different layers and architectures of a data warehouse, including the Inmon and Kimball approaches. Additionally, the course covers essential topics such as data modeling, including Kimball's four-step process and the comparison between column store and row store. Participants will also learn about data preparation and cleaning, as well as the differences between ETL (extract, transform, load) and ELT (extract, load, transform) processes. The course concludes with an exploration of cloud data warehouses. By completing this course, participants will acquire a comprehensive understanding of data warehousing basics, enabling them to effectively contribute to the data revolution within their organizations.