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Data Warehousing Concepts and key features

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Data warehousing is an integral part of any effective business intelligence endeavour which help in determine effectiveness of business processes, create policy, forecast trends, analyse the market and much more. In below tutorial , we will talk about Data Warehousing Concepts , its features and types. We will also talk about the architecture of Data warehouse .

Data Warehousing Concepts

  • A data warehouse is a relational/multidimensional database that is designed for query and analysis rather than transaction processing
  • A data warehouse usually contains historical data that is derived from transaction data
  • It separates analysis work load from transaction workload and enables a business to consolidate data from several sources.

Data Warehousing Concepts

Data Warehousing Concepts

Data warehouse Key Features

Below are the main characteristics of a data warehouse which has to be fulfilled.

Subject Oriented

Data warehouse is Subject Oriented , because it helps you in analyzing the information related to a subject. Example , you want to see sales of a new product in different regions. It mainly focuses on modelling of data for better analysis and decision making.


Data warehouse store data from different heterogeneous data source into common consistent format. All common issue like format , naming conflict , inconsistencies are taken during ETL process.


Once data is stored in data warehouse , data should not change.

Time Variant

The Data in Data Warehouse is identified with a particular time period. Example what is the normal sales of  a  product during Dec month  in last few year.

Check here for Data warehouse vs operational data

Data Warehouse Utilities Functions

The following are the functions of Data Warehouse Utilities:

  • Data Extraction – As a life cycle of Data ware housing  , data Extraction is the first step which involves gathering the data from multiple heterogeneous sources .
  • Data Cleaning – This process involves filtering unnecessary data  , correcting erroneous data
  • Data Transformation – Data Transformation involves converting data from legacy format to warehouse format.
  • Data Loading – Data Loading involves sorting, summarizing, consolidating, checking integrity and building indices and partitions.
  • Refreshing – Refreshing involves updating from data sources to warehouse.

Check here for Data warehouse architecture

Software Tools:

Various tool being used for data warehousing projects are :

ETL Informatica
Database Teradata
Reporting Cognos
 Business Objects
Data Quality QualityStage
Business Objects

Sources :



So in above article we have gone through the basic of Data warehousing concepts . We will cover more details like , basic architecture of data warehouse , OLAP VS OLTP in our upcoming tutorial.

The Author

Alisha Lamba

Hello Friends , I am Alisha Lamba .I love to write article on latest technologies like Informatica , ETL , data warehouse , SQL-PL SQL
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