Difference Between Data Warehouse and Data Mart

Data analysis is one of the most sought after need for any organization. Analysis requirements gather speed and momentum especially if the organization grows up over a period spanning into multiple units and divisions.

At any point in time, an entity would like to assess data to understand and/or to make decisions related to the entire unit or a sub-division. Data Warehouse and Data Mart are the most preferred tools being utilized in such scenarios.

Data Warehouse and Data Mart perform the same task viz. data analysis, however, they have subtle differences especially when it relates to the users being served.

Data Warehouse vs Data Mart

The difference between Data Warehouse and Data Mart is that Data Warehouse is a setup for analyzing data at an overall organizational level, while Data Mart is a subset of Data Warehouse and is utilized for analyzing data for specific domains/users.

Data warehouse vs Data mart

However, the above is not the only difference. A comparison between both the terms on certain parameters can shed light on subtle aspects:


Comparison Table

Parameter of ComparisonData WarehouseData Mart
MeaningSystem used for storing, retrieving, managing, reporting and analyzing large amounts of any type of dataData Mart is a subtype or subset of Data Warehouse
PurposeFor analysis of dataUsed for analysis of data but targeted or designed for certain groups or users
Implementation perspectiveMore time due to complex nature and ability to handle large dataLess time due to focus on specific areas only
Subject AreaNot focussed on any specific domains or subjects, it is utilized for the entire business as a wholeIt is subject-oriented, For example, analysis of data related to the human resources department
Amount of dataYesNo, because it is specific to some users
Macro level or micro levelUsed for the entire organizationFocussed only for certain users, hence can be considered as being suitable at a micro level
Which one is more useful?Depends on specific needs, but overall can be considered as more useful since it provides the information of the entire business (including all departments)Depends on specific needs, but overall can be considered as less helpful as it restricts to some domains/user groups


What is Data Warehouse?

Data Warehouse is the most preferred system for the management of voluminous data. Data Warehouse can be called as a powerful tool for analyzing data.

Data Warehouse is an informational set up to scrutinize, investigate, and analyze cumbersome and huge volumes of data which can be either historical or current. 

Data Warehouse works on the philosophy of gathering data from numerous sources or applications, processing the same, and finally conducting analysis.

This process helps in generating numerous summaries and customized reports for management decision making. One of the interesting features of Data Warehouse is that the data stored is not erased when new data is being added.

Data Warehouse is a boon to an organization so far as data analysis is concerned.

Data Warehouse is principally utilized for reporting, compressing, analyzing, investigating, integrating and summarizing data for making judgments and determinations related to the data.

Data Warehouse embraces sophisticated techniques to enable speedy search and accurate analysis.

Data Warehouse has some disadvantages which stop certain organizations from implementing the same. Some of the main demerits include expensive implementation and ongoing maintenance.

Also, if the data involved is too complex and voluminous the processing time may reduce considerably.

data warehouse

What is Data Mart?

Data Mart is a part(type) of Data Warehouse.

In simple terms, Data Mart is the access layer of a Data Warehouse environment, which is utilized to distribute data to specific users. Data Mart can be considered as a subset (and also an important one) of Data Warehouse.

Data Mart is subject or target-oriented, meaning it is built to meet the needs of particular groups or departments within an organization.

For example, the human resources division of the organization may be interested in analyzing data of retention and resignation trends. In such cases, the Data Mart will help generate the needed results. 

Data Mart is simple and easy to manage and comes at less cost. Data Mart utilizes limited amounts of data and processes the same quickly.

As Data Mart focuses only on certain specific users/sectors it is a boon to assessing data at a micro-level or specific business lines.

Data Mart has some shortcomings. For example, Data Mart can pull data only from limited/few sources, can store only a limited amount of data, and will have certain size limitations.

Also, as the organization grows there may be a tendency to create too many Data Marts which can be a complex process. Data Mart cannot be considered an enterprise-wide platform for data analysis solutions.

data mart

Main Differences Between Data Warehouse and Data Mart

  1. Data Warehouse is a system for managing and analyzing huge amounts of data. Data Mart is a type of Data Warehouse.
  2.  Data Warehouse manages data from all departments/business as a whole. Data Mart focuses on specific domains/users/groups.
  3.  Data Warehouse implementation and design is a complex process and takes time. Data Mart design and implementation is easy and takes less time.
  4.  Data Warehouse can take large amounts of data but there will be more time taken for processing. Data Mart only takes less data for processing but will process quickly.
  5.  Data Warehouse size range is quite large (maybe more than 1TB). Data Mart size is small (only in GB).
  6. Data Warehouse is more useful for an organization as a whole. Data Mart is more helpful for a single domain/department.
Difference Between Data Warehouse and Data Mart


  1. https://go.gale.com/ps/i.do?id=GALE%7CA18993844&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00010782&p=AONE&sw=w
  2. https://dl.acm.org/doi/abs/10.1145/313310.313345
  3. https://ieeexplore.ieee.org/abstract/document/6108446/
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