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According to Kamble, Desai & Vartak (2015), the last five years have been characterized with an explosive growth in data warehousing in the quality of services and in the number of products offered for the adoption of the data warehousing technologies. Data warehousing comprises of decision support technologies that enable a knowledge worker that is a manager, executive, analyst, or any other user in making decisions in a timely manner. A data warehouse supports the online analytical processing (OLTP), the performance, and the functional requirements that are different from those in online transaction processing applications to those supported by the operational databases. This paper will seek to offer a roadmap to technologies of data warehousing by focusing on the data warehousing process and its benefits to business organizations.
Data warehousing technology has grown to accommodate the large quantity of electronic data that is stored by organizations today. This growth is brought about by the need to make use of data to achieve goals and objectives beyond the normal daily processing tasks. For example, a large organization that has a number of branches may require senior managers to quantify and to conduct an evaluation of how individual branches are contributing to the global business performance (Lichtenberger, 2001). The corporate database is used to store data from these branches. In order to meet the needs of the manager, tailor-made SQL queries can be applied to retrieve the data required. For the process to be successful, database administrators have to formulate first the desired query after a close study of the database catalogs. The query is then processed to offer outcomes in a spreadsheet format.
Why Data warehousing?
In the last decade, database designers noted that the traditional approach of data processing, storage, and retrieval was hardly feasible since it demanded a lot of time and resources and sometimes it would not yield the desired results. In addition, the analytical queries combined with transaction routine queries would slow down the system hence failing to meet user needs on the type of query applied. This led to the design of the current advanced data warehousing processes, which brings a separation between two online processing platforms; analytical and transaction processing. A new information repository, which makes an integration of general data from several sources, made this possible. This design further allows for arranging properly the data formats for analysis and evaluation hence accommodating for both planning and a speedy decision-making process (Lichtenberger, 2001).
The purpose of the data warehousing process is to make operational data available to decision support applications such as ASA (Application Service Architecture).
Steps of data warehousing process aim to
Statisticians – These are the high-end users of data warehouse. They only require to be pointed to the database and to be given instructions on how to access the data. Their role involves determining the times of the day when they can best perform large queries for retrieving data for analysis using their skill and organizational tools.
Knowledge workers – Are engaged with data warehouse design and placing demands on the ongoing data warehouse operations team for support and training.
Information Consumers – these interacts with the data warehouse through work product of others and feedback gathered from them can improve information sites over time.
Executives – they are a special type of the information consumer group but can issue their own queries to know the progress of the organization and to keep up with the trends in the market.
Benefits of Data Warehousing