2015Communications of the IIMAOpen access

Optimizing Data Warehousing Startegies

Joseph O. Chan

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Abstract

Database technologies have evolved over the last two decades into different constructs to support the ever-growing information needs for organizations spanning the spectrum of operational and analytical processing. The paper examines the characteristics of transactional databases, operational data stores, data warehouses and virtual data warehouses. A framework is developed for an optimal data warehousing strategy based on organizational needs classified by the types of business processes defined by the requirements of supporting functional areas and the levels of decision structures. Enterprise architecture is described to provide an integrated and complimentary view of various data warehousing constructs.

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Database technologies have evolved over the last two decades into different constructs to support the ever-growing information needs for organizations spanning the spectrum of operational and analytical processing. The paper examines the characteristics of transactional databases, operational data stores, data warehouses and virtual data warehouses. A framework is developed for an optimal data warehousing strategy based on organizational needs classified by the types of business processes defined by the requirements of supporting functional areas and the levels of decision structures. Enterprise architecture is described to provide an integrated and complimentary view of various data warehousing constructs.

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Available abstract

Database technologies have evolved over the last two decades into different constructs to support the ever-growing information needs for organizations spanning the spectrum of operational and analytical processing. The paper examines the characteristics of transactional databases, operational data stores, data warehouses and virtual data warehouses. A framework is developed for an optimal data warehousing strategy based on organizational needs classified by the types of business processes defined by the requirements of supporting functional areas and the levels of decision structures. Enterprise architecture is described to provide an integrated and complimentary view of various data warehousing constructs.

Key concepts: Data warehouse, Computer science, Database, Online analytical processing, Architecture, Business intelligence, Data science, Knowledge management

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