Data Warehouse Characteristics

So, Data warehouse is an information system comprising single or multiple sources of historical and commutative information. Further, this simplifies the organization’s monitoring and reviewing process. Also, it is a single version of reality for any company to make and predict decisions.

Characteristics of Data Warehouse

Moreover, the following features of a data warehouse are used at Mergen IT:

  • Subject-Oriented
  • Integrated
  • Time-variant
  • Non-volatile


So, a data warehouse is subject-oriented as it provides information about a topic rather than the ongoing operations of companies. Thus, sales, marketing, distribution, etc. can be these topics.

Further, nor does a data center concentrate on ongoing operations. Also, instead, it put emphasis on modeling and analyzing decision-making data. So, it also offers a clear and succinct view of the specific topic by removing results that do not help the decision-making process.


Also, integration in Data Warehouse means setting up a specific unit of measurement from the dissimilar database for all similar data. So, it is also a common and widely acceptable way to store the data in the data warehouse.

Further, through integrating data from various sources such as a mainframe, relational databases, flat files, etc., a data warehouse is built. In addition, the naming conventions, format and coding must be clear.

Also, this integration allows for analyzing data ineffectively. So, it is necessary to ensure continuity in naming conventions, measurements of attributes, the structure of encoding, etc.

Three separate applications are A, B, and C in the above case. Gender, date, and balance are the information store in these applications. But, in a different way, the information of each program is stored.

  • Gender A Application field store logical values like M or F
  • Infield Application B gender is a numerical value,
  • In C Application, the gender field stored in the form of a character value.
  • Same is the case with Date and balance

However, after the process of transformation and cleaning, all these data are storeĀ in a common format in the data warehouse.


Compared to operating systems, the data warehouse’s time span is very extensive. It contains, explicitly or implicitly, an element of time.

One such place where time variation in data warehouse data display is in the record key structure. That primary key in the DW should have an element of time whether implicitly or explicitly. Like the day, the month of the week, etc.

Another consequence of the time variation is a modification or adjustment is not possible once the information is into the warehouse.


A data warehouse is also non-volatile, meaning that when new data inserts in it, previous data will not be deleted.

Data is read-only and updated on a regular basis. This also assists with evaluating historical data and understanding what and when it occurred. It does not include frameworks for payment, recovery and competitiveness regulation.

In a data warehouse environment, tasks such as removing, upgrading, and adding are out in a functional software setting are excluding. Only two types of data storage operations are there.

  1. Data loading
  2. Data access

Here are some major differences between Data Warehouse and Application

Operational Application Data Warehouse
Complex systems need to be coded to ensure the high quality of the final product is preserved by software update processes.This type of problem does not occur because the update of the data is not carried out.
To ensure minimum redundancy, information is stored in a structured form.Data is not stored in a standard form.

The technology needed as its deadlock is quite complex to support transaction problems, data recovery, rollback, and resolution.

It offers relatively simple engineering.

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