Abstract

Data warehousing and cloud computing are modern trends in computing businesses. Data warehouse (DWH) is subject-specific, time-changing, non-volatile, integrated collection of data and it is a process that helps decision maker in the process of informed decision making. It is also an integrated software component of the cloud which provides support for timely and accurate response to complex queries. The complex analytics involving huge amounts of data with the help of tools such as: Online Analytical Processing (OLAP) and data mining are built on DWH model. Similarly, cloud computing provides a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider’s interaction. These computing infrastructures when allowed to work together can provide decision makers with immense benefits at minimal costs. Therefore, it is pertinent to consider the contending issues and challenges faced by bridging the gap between DWH and cloud computing as well as proffer possible solutions. The future directions and conclusions are also pointed to and drawn from the paper.

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