IT DATA WAREHOUSING

IT Data Warehousing

IT Data Warehousing

Introduction

Data warehousing (DWG), which implements a shared data warehouse (DW) and/or subject-oriented data mart (DM), has become a central process for decision support-oriented data management. From its beginning as a little-understood experimental concept only a few years ago, it has reached a stage where nobody questions its strategic value. Statistical indicators and surveys show that the number of companies that already own or are currently building the decision support platform is exploding; large enterprises are involved in at least one or more related projects . Databases tuned for operational and transactional use are, in general, not structured to satisfy information demand from managers. There is a growing utility gap between operational systems and decision support systems, making DWG increasingly essential to organizational decision-makers. Its vital role continues to expand as the market becomes more customer-centered and demands sophisticated business intelligence.

The DWG environment contains a large volume of historical data that are both atomic and summarized. Because of the architectural complexity, high implementation cost, and uncertain return on investment, it has been a controversial concept and has sometimes encountered managerial opposition . Despite early skepticism, DWG is spreading through enterprises, as evidenced by a report that 85-90% of the Fortune 500 companies have either adopted or plan to adopt it [13].

Various motives for deploying DWG have been discussed. Above all, industry-wide emergence of stiff competition forces organizations to adopt such measures to improve business competency. Corporate success increasingly depends on the mobilization of business intelligence. Increasing deregulation, globalization, and partnering are major driving forces of DWG in the telecommunications industry . Growing popularity of virtual processes in the form of distributive computing, telework, electronic channel management, and virtual corporations is further fueling the need for the integration of information platforms.

Because DWG is not a product but a process that enables a single view of a business , its adoption inevitably entails or results in appropriate re-engineering of business processes. The key component is a “single, complete, and consistent store of data obtained from a variety of sources and made available to end-users in a way they can understand and use in a business context ”. DWs and DMs differ from operational databases by containing more subject-oriented, integrated, time-variant, non-volatile, stabilized, and ad hoc-oriented data for decision aid . A DM in general is a subset (i.e. a subject area) of associated DW. The former contains granular (or atomic) and/or summarized data that are necessary for a particular business application. Despite the increasing value of DWG, there has been little research on its planning and implementation from a holistic perspective. This case study is intended to investigate the project management approach taken at a large enterprise for a pilot DWG project.

Data warehousing benefits

The company studied provides individual health and accident insurance services; it has more than 6 million customers and over US$ 80 billion of life insurance in force. The company developed a long-term plan to invest US$ 100 million in four phases to improve IT infrastructure ...