Everything about Data warehouse
Centralized storage of knowledge
In computing, a data warehouse, also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. Data warehouses are central repositories of data integrated from disparate sources. They store current and historical data organized in a way that is optimized for data analysis, generation of reports, and developing insights across the integrated data. They are intended to be used by analysts and managers to help make organizational decisions. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Data warehouseA 5-minute orientation
- Skim a recent paper: Healthcare data security and privacy in Data Warehouse architecturesInfluential work since 2022
- Pick up a classic book: The data warehouse toolkitThe most-reprinted book on the subject
- Read the landmark paper: Enhancing data quality in data warehouse environmentsCited 160 times
- Go sideways: Data martA closely related topic
- Go sideways: Dimensional modelingA closely related topic
📖 Definitions
Noun A collection of data, from a variety of sources, organized to provide useful guidance to an organization's decision-makers.
🏆 Landmark papers (most cited)
Enhancing data quality in data warehouse environments
A clinician friendly data warehouse oriented toward narrative reports: Dr. Warehouse
The data warehouse and data mining
Data mining a diabetic data warehouse
Building the data warehouse
COVID-WAREHOUSE: A Data Warehouse of Italian COVID-19, Pollution, and Climate Data
The LCB Data Warehouse
Clinical Data Warehouse
🆕 Influential since 2022
Healthcare data security and privacy in Data Warehouse architectures
Data-driven optimization for automated warehouse operations decarbonization
Data Warehouse Design for Big Data in Academia
Warehouse CITY – An open data product for evaluating warehouse land-use in Southern California
Custom data quality mechanism in Data Warehouse facilitated by data integrity checks
📚 Books worth reading
The data warehouse toolkitRalph Kimball, Margy Ross · 1996
Implementing SAP S/4HANA FinanceAnup Maheshwari · 2016
SAP HANABerg Dr · 2012
Data warehouseBarry Devlin · 1996
Data-Warehouse-Systeme kompaktKiumars Farkisch · 2011- 📕SAP ERP HCMDirk Liepold · 2013
- 📕Sales and Operations Planning with SAP IBPJeroen Kusters, Raghav Jandhyala · 2018
- 📕Customizing extended warehouse management with SAP ERPVarun Uppuleti · 2010
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Data mart A data mart is a structure/access pattern specific to data warehouse environments. The data mart is a subset of the data warehouse that focuses on a specific…
- Dimensional modeling Dimensional modeling is part of the Business Dimensional Lifecycle methodology developed by Ralph Kimball which includes a set of methods, techniques and…
- Star schema In computing, the star schema or star model is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and…
- Outline of databases The following is provided as an overview of and topical guide to databases: Database – organized collection of data, today typically in digital form. The…
- Online analytical processing In computing, online analytical processing (OLAP) (/ˈoʊlæp/), is an approach to quickly answer multi-dimensional analytical (MDA) queries. The term OLAP…
- Data vault modeling Datavault or data vault modeling is a database modeling method that is designed to provide long-term historical storage of data coming in from multiple…
- Fact table In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or…
- Essbase Essbase is a multidimensional database management system (MDBMS). The platform provides tools to build data analytic applications. Arbor Software developed…