data warehouse

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Data warehouse refers to a set of data that is collected, categorized and stored from various information sources of the organization. In other words, “a data warehouse is a subject-oriented, integrated, time-varying and non-volatile collection of data that supports decision-making management”. The main purpose of creating a data warehouse is to use the data produced and stored by operational systems in the data warehouse and to use them correctly in the decision-making process at strategic levels. It is also the future.

Necessity of employment

Since performing statistical operations and complex reports have a very heavy workload for the database servers of operational systems, the existence of a data warehouse means that such operations do not affect the activity of the organization’s application programs (OLTP). By creating a data warehouse, a suitable and stable platform is provided for the preparation of fast, integrated and diverse reports. A data warehouse can be seen as an information database that is kept separately from the operational databases of the organization and is ultimately used by analytical tools.

Creation steps

In general, the construction of a data warehouse, in the form of a project, includes the following main steps:
  • Extracting operational data from different databases into a single repository
  • Expanding and transforming data
  • Loading the converted data into a database
  • Generating pre-calculated data values ​​to increase reporting speed
  • Preparation of an analytical reporting tool and business intelligence


Due to the fact that the choice of tools to create a data warehouse depends a lot on the type of organization’s activity and the dependence of processes on each other, for this reason, after the Feasibility Study, the selection of tools to create a data warehouse is done. But generally one of the two tools SQL Server or Oracle are suitable for this part.

Final tools

In order to make data warehouse information available to users, various tools are used in data warehouse architecture, which are called “final tools”.
The category of final tools includes the following:
  • Query and reporting tools
  • Developed application tools
  • Executive information systems tools
  • Simultaneous analytical processing tools
  • Data mining and analytical tools
Most of these tools fall into the category of business intelligence.
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Purpose and application

The primary goal in Data Warehouse architecture is to create a centralized data warehouse with specified and standard definitions. After this stage, analytical reports can be created on the data warehouse using powerful business intelligence tools such as QlikView or other tools such as OLAP-Based. In such a way that after forming a data warehouse and cleaning and collecting data in it, an analytical tool is placed on it and a platform for analytical, statistical, data mining and management dashboards is provided.
The opposite figure shows an overview of the combination of a business intelligence tool with a data warehouse.

Advantages of using data warehouse

  • It provides accurate information about the previous and current status of the organization.
  • It provides an integrated and refined memory for the organization.
  • It reduces the costs of software development and their integration.
  • It provides the information of the organization in the form of themes and information from several areas.
  • It can be used as a platform for analytical, statistical and management tools.
  • It provides the ability to report and analyze quickly and at low cost.
  • It enables the transformation of raw and scattered data into integrated and strategic information.