Data Warehouse and Data mart overview, with Data Marts shown in the top right.
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence.[1] Data warehouses are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating reports. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.[2]
The basic architecture of a data warehouse
The data stored in the warehouse is uploaded from the operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the data warehouse for reporting.
Extract, transform, load (ETL) and extract, load, transform (ELT) are the two main approaches used to build a data warehouse system.
^Dedić, Nedim; Stanier, Clare (2016). Hammoudi, Slimane; Maciaszek, Leszek; Missikoff, Michele M. Missikoff; Camp, Olivier; Cordeiro, José (eds.). An Evaluation of the Challenges of Multilingualism in Data Warehouse Development. International Conference on Enterprise Information Systems, 25–28 April 2016, Rome, Italy (PDF). Proceedings of the 18th International Conference on Enterprise Information Systems (ICEIS 2016). Vol. 1. SciTePress. pp. 196–206. doi:10.5220/0005858401960206. ISBN 978-989-758-187-8. Archived (PDF) from the original on 2018-05-22.
^"What is a Data Warehouse? | Key Concepts | Amazon Web Services". Amazon Web Services, Inc. Retrieved 2023-02-13.
Datawarehouse automation (DWA) refers to the process of accelerating and automating the datawarehouse development cycles, while assuring quality and...
A data mart is a structure/access pattern specific to datawarehouse environments, used to retrieve client-facing data. The data mart is a subset of the...
any datawarehouse development effort. They detail metadata on each piece of data in the datawarehouse. An essential component of a datawarehouse/business...
datawarehouse appliance (DWA) was coined by Foster Hinshaw for a computer architecture for datawarehouses (DW) specifically marketed for big data analysis...
quality like a datawarehouse. A data lakehouse architecture attempts to address several criticisms of data lakes by adding datawarehouse capabilities...
Analytics is a fully managed cloud datawarehouse. Azure Data Factory, is a data integration service that allows creation of data-driven workflows in the cloud...
flow from databases into datawarehouses. Business analysts, data engineers, and data scientists can access datawarehouses using tools such as SQL or...
as opposed to the practice in other datawarehouse methods of storing "a single version of the truth" where data that does not conform to the definitions...
made to enterprise data sources. For instance it can be used for incremental update of data loading. CDC occurs often in data-warehouse environments since...
An operational data store (ODS) is used for operational reporting and as a source of data for the enterprise datawarehouse (EDW). It is a complementary...
Investigative DataWarehouse (IDW) is a searchable database operated by the FBI. It was created in 2004. Much of the nature and scope of the database is...
feasibility of large-scale data integration. The datawarehouse approach offers a tightly coupled architecture because the data are already physically reconciled...
A warehouse is a building for storing goods. Warehouses are used by manufacturers, importers, exporters, wholesalers, transport businesses, customs, etc...
A data hub is a center of data exchange that is supported by data science, data engineering, and datawarehouse technologies to interact with endpoints...
as their data volumes grow. Customers can scale their datawarehouse through the Db2 Warehouse on Cloud web console or API. Data security: Data is encrypted...
European DataWarehouse (EDW) is a Securitisation Repository designated by both the European Securities and Markets Authority (ESMA) and the Financial...
platform as a service offering on Microsoft Azure. Azure MPP Azure SQL DataWarehouse is the cloud-based version of Microsoft SQL Server in a MPP (massively...
common source for data is a data mart or datawarehouse. Pre-processing is essential to analyze the multivariate data sets before data mining. The target...
possible solution is to make use of shadow tables. Database Datawarehouse "Incremental Data Load vs Full Load ETL: 4 Critical Differences - Learn | Hevo"...
filled with disparate data sources including multiple datawarehouses, data marts, and/or data lakes, even though a DataWarehouse, if implemented correctly...
remanence Data science Data set Data structure Data visualization Datawarehouse Database Datasheet Data-driven programming Data-driven journalism Data-driven...
management Datawarehousing and business intelligence and Analytics Business intelligence Data analysis and data mining Datawarehouse and data mart Data analytics...
customer record (or part of it) and the warehouse dispatch system might also need a copy of some or all of the customer data (e.g., shipping address). In cases...
Global Information
