What are the types of data warehouse quality?

Data MiningDatabaseData Structure

A data warehouse architecture exhibits several layers of data in which data from one layer are changed from data of the lower layer. Data sources, also known as stored in open databases, form the lowest layer. They include structured data saved in the open database system and legacy systems, or unstructured or semi-structured data saved in files. There are several types of success associated with data warehousing which are as follows −

  • Economic success − The data warehouse has a specific impact on the bottom line.

  • Political success − People like what is done. If the data warehouse is not required, it’s accessible that it failed politically.

  • Technical success − This is the simplest to perform but don’t defeat your users with too much technology. Success also defines that the chosen technologies are suitable for the task and are used correctly.

There are various types of data warehouse quality which are as follows −

Business Quality − It is directly associated with economic success, business quality is the ability of the data warehouse to support data to those who required it to have a specific impact on the business. Business quality is made up of business drivers, or approach that point out an organization’s strategic plans. Therefore organizations should be concerned with how well the data warehouse support achieves these drivers, including changing economic aspects, environmental concerns, and government regulation.

Information Quality − Information doesn’t have value if it is not utilized. Thus to have information quality, the target should be on the integration of data into the texture of business processes, not on data quality itself. Information quality is the key to political success. Success in this area defines providing awareness, access tools, and the knowledge and skills to handle what they are given.

Technical Quality − Technical quality is the capability of the data warehouse to satisfy the user’s dynamic data required. Wells defines four important technical quality factors. The first is “reach,” or whether the data warehouse can be used by those who are best served by its existence.

In today’s information-dependent business climate, organizations are required to reach beyond the narrow and generally user base of suppliers, users, and a few managers. The range is also necessary. This represents a range of services supported by the data warehouse. For instance, Web enablement, including Hotmail, are services that enable users to get data from wherever they are.

Manoeuvrability is the capacity of the data warehouse to acknowledge changes in the business environment. The data warehouse doesn’t continue fixed, so Manoeuvrability becomes particularly essential.

Updated on 23-Nov-2021 10:34:00