What is Data Warehouse in Business Intelligence?
Tags: datawarehouse, businessintellegence, bi, clouddatawarehousing
Published: 2020-12-13 12:10:21

In business intelligence, data warehouses serve as the backbone of data storage. [Data warehousing](https://www.cloudmoyo.com/blog/data-architecture/what-you-need-to-know-about-advanced-data-warehousing/) and [business intelligence](https://www.1keydata.com/datawarehousing/business-intelligence.php) are terms used to describe the process of storing all the company’s data in internal or external databases from various sources with the focus on analysis, and generating actionable insights through online BI tools.

A [data warehouse](https://www.1keydata.com/datawarehousing/data-warehouse-definition.html) is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process.


[Business intelligence (BI)](https://olap.com/learn-bi-olap/olap-bi-definitions/business-intelligence/) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.


**Data warehouse Architecture :**



![data-warehouse-architecture](https://dev-to-uploads.s3.amazonaws.com/i/dbyumxut65te4gku34x9.png)
 
**Operational System**
An operational system is a method used in data warehousing to refer to a system that is used to process the day-to-day transactions of an organization.

**Flat Files**
A Flat file system is a system of files in which transactional data is stored, and every file in the system must have a different name.

**Meta Data**
A set of data that defines and gives information about other data.
Meta Data used in Data Warehouse for a variety of purpose, including:

Meta Data summarizes necessary information about data, which can make finding and work with particular instances of data more accessible. For example, author, data build, and data changed, and file size are examples of very basic document metadata.


**Lightly and highly summarized data**
The area of the data warehouse saves all the predefined lightly and highly summarized (aggregated) data generated by the warehouse manager.

The goals of the summarized information are to speed up query performance. The summarized record is updated continuously as new information is loaded into the warehouse.

**End-User access Tools**
The principal purpose of a data warehouse is to provide information to the business managers for strategic decision-making. These customers interact with the warehouse using end-client access tools.

The examples of some of the end-user access tools can be:
[*Reporting and Query Tools*](https://blog.panoply.io/top-25-reporting-tools-and-how-to-choose-the-best-option)
[*Application Development Tools*](https://www.selecthub.com/business-intelligence-tools/)
[*Executive Information Systems Tools*](https://www.g2.com/software/executive-information-system)
[*Online Analytical Processing Tools*](https://www.predictiveanalyticstoday.com/online-analytical-processing-tools/)
[*Data Mining Tools*](https://www.softwaretestinghelp.com/data-mining-tools/)

**Data Warehouse in the Cloud**:

A [cloud data warehouse](https://www.scnsoft.com/analytics/data-warehouse/cloud) is a system, which uses the space and compute power allocated by a cloud provider to integrate and store data from disparate data sources. It is employed for data structured storage, analysis and reporting.

[**Cloud Data Warehouse vs Traditional Data Warehouse Concepts**](https://panoply.io/data-warehouse-guide/data-warehouse-concepts-traditional-vs-cloud/)

**Difference Between** [**Business Intelligence and Data Warehouse** :](https://www.educba.com/business-intelligence-vs-data-warehouse/)

![Business-Intelligence-vs-Data-Warehouse](https://dev-to-uploads.s3.amazonaws.com/i/snxvdowliy6pcbnfsvlc.jpg)