Data mart is often interchanging-ly used to mean a data warehouse. If you are not proficient, you may be one of those who said data mart while it is supposed to be a data warehouse. This article will explain the concept of data mart and how it is different from a data warehouse.
Data mart definition
In simple terms, a data mart is a repository of data that is designed to serve a particular community of knowledge workers. Data is gathered from operational data and other sources that is designed to serve a particular community of knowledge workers.
In other words, data mart is a simple form of a data warehouse that is focused on a single subject (or functional area), such as Sales, Finance, or Marketing. It is important to note that definition of data warehouse does not mentions “to server a particular community”. That is infact the major distinction between a data warehouse and data mart.
How data mart is different from data warehouse?
A data warehouse is a central repository for all an organization’s data. The goal of a data mart, however, is to meet the particular demands of a specific group of users within the organization, such as human resource management (HRM). Generally, an organization’s data marts are subsets of the organization’s data warehouse.
A data mart is basically a condensed and more focused version of a data warehouse that reflects the regulations and process specifications of each business unit within an organization. Following bullet points should further clarify the difference:
| Data warehouse | Data mart |
| Holds multiple subject areas | Often holds only one subject area- for example, Finance, or Sales |
| Holds very detailed information | May hold more summarized data (although many hold full detail) |
| Works to integrate all data sources | Concentrates on integrating information from a given subject area or set of source systems |
| Does not necessarily use a dimensional model but feeds dimensional models. | Is built focused on a dimensional model using a star schema. |
Why we need data marts?
While many of the reasons to create a data warehouse very much apply for creating a data mart, let us focus on why any organization has to create a data mart instead of a data warehouse.
- To gain easy access to frequently needed data
- To create collective view by a group of users
- To improve end-user response time
- It is easy to create data mart compared to creating a data warehouse
- It will cost less compared to cost of implementing a full data warehouse
- Potential users of the data mart are more clearly defined than in a full data warehouse
- Data mart will contain only business essential data and is less cluttered
An important take away from the article is the fact that a data warehouse tends to be a strategic while a data mart tends to be tactical and aimed at meeting an immediate need.
