In the process of decision-making, the post-decision monitoring and evaluation are tagged on a company’s data warehouse. The data warehouse is relied upon by the Directors as a copy of transactions structured and designed for querying and reporting. The data can be converted into business intelligence by observing management decisions based on facts. The company is hence able to gain a competitive advantage in the market. For transactions to be completed within a stipulated time frame there is a need to retrieve reports and queries about the operations of the company. Data warehousing is an architecture that uses separate servers for querying and reporting is usually the least expensive in most organizational expeditions.
Data warehousing is not an individual product, instead, it is a comprehensive development process of establishing a decision support mechanism in a business to utilize a wide range of data. To the Directors and strategists, the data warehouse is a pool from which applications are designed to support managers in their executive businesses. Data warehousing is a practical exploration of the technological innovations in traditional manual data practices. As an executive information system, a data warehouse caters to the analytical and information needs of the managers. This process calls for both business and technical support and expertise. Apart from the managers, another beneficiary of the warehousing project is the business community. Access to accurate and various consolidated authorities by the communities is realized through the data warehouse. The warehouse is put in an environment where business strategies can be sourced and inferred. Information from diverse sources is linked and harmonized to establish long-term strategies.
Information systems have long been used to gather and store information to produce specific reports for workers and to produce aggregate reports for managers. However, senior managers rarely use these systems directly and often find the aggregate information to be of little use without the ability to explore underlying details, (Watson & Rainer, 1991). Relevant information to the business community is timely and accurate. The information is tailored to meet the executive information needs. Information about the interactions of the company and the environment is made available to all stakeholders. The winners in this process are those who are intelligent and aggressive enough to venture into data warehousing. Companies across the globe have their success connected to a good data-warehousing scheme. Knowledge from the business environment connected to the available data is pivoted to the success of the business. A core point in business is the ability to manage and appropriately interpret the data available in the company. A major key trend is to use the data warehouse to predict and plan in advance and not only reporting on past success.
Losers in the data warehouse project
What distinguishes the winners and the losers in data warehousing is good intelligence. Winners as opposed to losers are those who have the minds to diversify into services that can help companies realize more profits. The losers are those relying on hardware and new products without any means of adopting the changing technological advancement. This company is going to suffer tremendously with a decline in the financial base. The losers are not far-sighted and in a short-term transaction. There is a great opportunity for innovative ventures in establishing a company’s warehouse, the losers shall lag and lose track in the business. The process of warehousing calls for the support of all like-minded stakeholders. It is a team effort that requires the spirit of innovative, able, and resourceful personnel.
Managing the data warehouse
Establishing the data warehouse presents another problem. Who should manage the data warehouse? The data warehouse positions a company to consume and maximize a wide range of data stores for the linkage of information from diverse sources. Data warehouse management is a key activity that will enable the company to control all the different versions of data, control the voluminous data. This includes keeping a constant evaluation and feedback about the data warehouse. Data management is the process of getting resources together to accomplish the desired goal. This comprises practices such as creating, identifying, distributing, and allowing innovations in the data warehouse. It is an extensive process that involves:
- The different types, sizes, formats, and data documents.
- Traceability of data and access of data.
- Access to authorized users of data and prevention of access to unauthorized users.
- Maintaining an archive of data
It requires experienced data warehouse architects and database designers to manage the warehouse. This is because the data warehouse requires different roles and usage of data. The analytical modeling of data is hinged on different skills and perspectives in the application of techniques. It is important to allow personnel that understands how to handle changing dimensions, snapshot data, complex dimensions, and multi-valued dimensions in a data application. The business and technical data warehouse team members are responsible for analyzing, extracting, storage and expanding the data dictionary. Business intelligence tools are very essential for managing and retrieving metadata. The process of transforming data into discreet information and availing it to the user should be timely. Data warehousing management requires a competent staff that can handle the large-scale collection, storage, and analyzing data. Maintenance of the data warehouse is expensive as there is a need to have a continuous adjustment of the data in line with the changing trend in the market. The data management of the data warehouse requires a competent staff able to direct, control, organize and mobilize resources to develop the data warehouse. These are the key values of management. The management of the data warehouse has its primary function in the satisfaction of the needs of the stakeholders. This entails creating valuable products, innovation, and improving the operations of the company. A data warehouse manager has the responsibility of coordinating and directing the storage of data in a company.
Data warehouse projects pose challenges to the manager. Technical and resourcing issues are the key challenges. This requires skilled personnel in managing the company’s data warehouse. This can only be successful in the presence of disciplined, understanding, and forecast managers. The success of the warehouse lies in the definition of the model the company will use to enhance optimum usage of the data warehouse.
The concept of data warehousing is intended to provide an architectural model for the transfer of data from operational systems to decision-making systems. This paper has adopted an analytical approach in investigating the major winners and losers in a data warehouse project. The system of collecting, refining, and data integration in a company’s first project is the pivot of this discussion. The paper views architecture in the context of a company’s effort to establish and maintain a warehouse. The success of the architecture cannot be divorced from the building, maintenance, and consumption of the data warehouse.
The evolution in the Company’s use of data warehouses is seen from the start points when a company adopts simple warehousing. More advanced sophisticated electronic data warehousing replaces the manual warehouse. It is evident from this discussion, that a data warehouse is a pivotal part of a company’s organization. For instance, it harmonizes all the data regardless of the source into a common model making the process of reporting and data-analyzing simple.
Consequently, data warehouses promote the companies operation by maintaining information. As a result, decision-making systems are supported in data that shows the actual company’s performance alongside the stipulated goals. The fact that the operating systems are divorced from the data warehouse means data can still be retrieved without slowing down the operating systems.
Data warehouses, on the other hand, have presented problems to companies. As much as it is a good managerial trend, this paper suggests the need to be aware of some of the obstacles and unpleasant scenarios that we can run into as a result of the data warehouse. Maintenance of a data warehouse over its life is very costly. The warehouse is not static and it has to be modified continuously, this involves training of staff and acquisition of new facilities. On the same note, a very slim distinction between the data warehouse and operational systems might lead to duplication. Data warehousing is a lifelong process in an organization and as this paper proposes, efforts should be made to integrate this into management. Researchers in data warehousing having been carried for a long time, this paper comes in to add knowledge in this field and provide an avenue for further research. The management of the data warehouse is responsible for the delivery of strategies for maintaining the warehouse.
- Greenfield, L. (2005). The Case for Data Warehousing. The Data warehousing center.
- Greenfield, L. (2005). The Case Against Data Warehouse. The Data Warehousing Information Center.
- Demarest, M. (2005). The Politics of Data Warehousing.
- Parkinson, J. (2005) Pack-rat Approach to Data Storage in Drowning IT.CIO Insight.