While implementing a Data Warehouse, there are a multitude of complex things to consider. Data Management is one of the most important aspects that need to be considered, aside from other things like physical server and network components.

In Data Management, the design of the Data Structure determines the smooth and successful implementation of the database that will power the Data Warehouse.

Since a Data Warehouse is a rich repository of all sorts of data – from company data history to data from outside data sources – it is always to a good idea to classify these data in order to get the relevant information and generate statistical reports for the company.

A subject area is the summary of all things that a Business Enterprise is interested in. It pertains to the collection of data information which has a relation to high level function of the organization. A conceptual model defines a subject area as the limit between systems or areas of interest within the organization. An example of data subject area would be Employee Subject Area which contains all entities and other data attributes pertaining to employees.

Despite the segregation of the high volume of disparate data coming from various data sources in a Data Warehouse, there is still no assurance of effectively looking for the most relevant data without any help from tools and other retrieving techniques. Using Data Keys for data subject can greatly help in the retrieval or important and relevant data from the database within the Data Warehouse.

Since Data Keys uniquely identify data occurrences in each data subject within the data resources, when a data consumer tries to look for a data, he is no longer challenged by sifting through the heavy volume. Instead, his search will be narrowed down because of the use of a key.

For example, without the help of a Data Key, when a data consumer want to look for the buying trend of say, people within the age range of 20-30 years old, he may be confronted with data coming all kinds of customers within the database.

But when the data consumers use a Data Key to identify the people within the 20-30 years old, his search will definitely be narrowed down. As a result, his search will be a lot faster and the computer server will not be burdened with intensive processing load.

A Data Warehouse itself is a subject-oriented information system which is designed for company support. It is an environment that organizes and provides reports in a manner that the business people can understand.

There are several layers in a Data Warehouse Architecture and one of the layers include extraction, cleansing and transformation of source information. This is the layer where Data Keys are attached to certain data so that it would be easy to find only the relevant data in the warehouse.

The Data Key is one of the important aspects of data structures used in general in the information technology field. In cryptography, a data key is a variable value which is added to a block of text or string. The encrypted data can only be opened by the key.

Data Key can also be an actual physical object that can store digital information and required to gain data access. A key analyzer is an associated program or mechanism to enable a computer to process data.