1998ACM SIGMIS Database the DATABASE for Advances in Information SystemsRequires access

Present and future directions in data warehousing

Paul Gray, Hugh J. Watson

Open publisher page 38 citations

Abstract

Many large organizations have developed data warehouses to support decision making. The data in a warehouse are subject oriented, integrated, time variant, and nonvolatile. A data warehouse contains five types of data: current detail data, older detail data, lightly summarized data, highly summarized data, and metadata. The architecture of a data warehouse includes a backend process (the extraction of data from source systems), the warehouse, and the front-end use (the accessing of data from the warehouse). A data mart is a smaller version of a data warehouse that supports the narrower set of requirements of a single business unit. Data marts should be developed in an integrated manner in order to avoid repeating the "silos of information" problem.An operational data store is a database for transaction processing systems that uses the data warehouse approach to provide clean data. Data warehousing is constantly changing, with the associated opportunities for practice and research, such as the potential for knowledge management using the warehouse.

About this research paper

What this paper is about

Many large organizations have developed data warehouses to support decision making. The data in a warehouse are subject oriented, integrated, time variant, and nonvolatile. A data warehouse contains five types of data: current detail data, older detail data, lightly summarized data, highly summarized data, and metadata. The architecture of a data warehouse includes a backend process (the extraction of data from source systems), the warehouse, and the front-end use (the accessing of data from the warehouse). A data mart is a smaller version of a data warehouse that supports the narrower set of requirements of a single business unit. Data marts should be developed in an integrated manner in order to avoid repeating the "silos of information" problem.An operational data store is a database for transaction processing systems that uses the data warehouse approach to provide clean data. Data warehousing is constantly changing, with the associated opportunities for practice and research, such as the potential for knowledge management using the warehouse.

Why it matters

OpenAlex reports 38 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Many large organizations have developed data warehouses to support decision making. The data in a warehouse are subject oriented, integrated, time variant, and nonvolatile. A data warehouse contains five types of data: current detail data, older detail data, lightly summarized data, highly summarized data, and metadata. The architecture of a data warehouse includes a backend process (the extraction of data from source systems), the warehouse, and the front-end use (the accessing of data from the warehouse). A data mart is a smaller version of a data warehouse that supports the narrower set of requirements of a single business unit. Data marts should be developed in an integrated manner in order to avoid repeating the "silos of information" problem.An operational data store is a database for transaction processing systems that uses the data warehouse approach to provide clean data. Data warehousing is constantly changing, with the associated opportunities for practice and research, such as the potential for knowledge management using the warehouse.

Key concepts: Data warehouse, Dimensional modeling, Computer science, Database, Metadata, Data extraction, Data element, Database transaction

Related papers

Back to paper searchBrowse research topicsOriginal source
Present and future directions in data warehousing — Research Paper | ScholarLens