Building the Data Warehouse
by W. H. Inmon · W.H. Inmon
Inmon's foundational text on the enterprise data warehouse: subject-oriented, integrated, time-variant storage feeding downstream data marts. Explains granularity, partitioning, and the operational data store, and gives you the top-down architecture that contrasts with Kimball's approach.
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More resources on Data Warehousing
kimballgroup.com
Kimball Group is a resource for data warehousing best practices, centered on the Kimball dimensional modeling methodology. The site features articles, white papers, and design guidance on star schemas, data warehouse architecture, and scalable analytics.
Data Warehousing Fundamentals
Welcome to Fundamentals of Data Warehousing, the third course of the Key Technologies of Data Analytics specialization. By enrolling in this course, you are taking the next step in your career in data analytics. This course is the third of a series that aims to prepare you for a role working in data analytics. In this course, you will be introduced to many of the core concepts of data warehousing. You will learn about the primary components of data warehousing. We’ll go through the common data warehousing architectures. The hands-on material offers to add storage to your cloud environment and configure a database. This course covers a wide variety of topics that are critical for understanding data warehousing and are designed to give you an introduction and overview as you begin to build relevant knowledge and skills.
tdwi.org
TDWI.org is a premier resource for data warehousing, BI, and analytics professionals, offering news, in-depth articles, research reports, webinars, training, and conference events to help practitioners design, implement, and optimize data warehouses and BI solutions.
The Data Stack Show
Weekly interview podcast produced by RudderStack in which hosts talk with data engineers, analysts and data scientists about building data infrastructure, pipelines, warehouses and data products, and about the tooling and organisational choices behind them. Listeners gain practitioner context on modern data stacks.
The Data Warehouse Toolkit
Kimball's reference on dimensional modeling and the full warehouse lifecycle, from requirements gathering through ETL design and BI delivery. After it you can design star schemas, plan fact and dimension tables, and sequence a warehouse build.
Advanced Data Warehousing
Capstone of IBM's Data Warehouse Engineer certificate. You build a MySQL OLTP source, a PostgreSQL staging warehouse with fact and dimension tables, shell-script ETL jobs on cron, and a Cognos or Looker Studio dashboard.