Data Warehouse Architecture

Start with the warehouse overview

The Data Warehousing mind maps offer a starting point for this topic. One introduces a data warehouse as a collection of integrated, subject-oriented databases that supports decision-making functions. Another describes it as a pool of data for decision-making and introduces characteristics such as integration and nonvolatility.

Begin with an overview map and note the characteristics it names. Then compare them with the questions in the warehouse architecture quiz, which asks about components, warehouse rules and OLAP characteristics. Use the map to revisit any terms that are unfamiliar.

Follow the architecture

A Data Warehouse mind map lays out data sources, a back-end tier, an ETL process and a warehouse tier. Use it to trace the parts named in the map and see how they are grouped. Other maps introduce operational data stores, enterprise data warehouses, real-time warehouses and data marts.

The fundamental big data architecture quiz covers operational data stores, staging areas, warehouses, data marts and analytical databases. Try it after exploring the maps. The advanced architecture quiz also covers enterprise data warehouses and big data, including comparison and integration. You can return to the maps between quizzes to review the terms.

Practice data mart concepts

The data mart flashcards describe a data mart as a subset of data stored in a data warehouse. They also introduce a dependent data mart. Use the deck to review those definitions, then look for data marts in the architecture maps and quizzes.

Place the topic in the unit

Data Warehouse Architecture is a section of Data Warehousing and OLAP in Databases and data science. The resources on this page connect warehouse components with decision support and OLAP questions. Choose a map or quiz and build a study sequence that suits you.