Key Difference between Data Warehouse and Data Mart
- Data Warehouse is a large repository of data collected from different sources, whereas Data Mart is only subtype of a data warehouse.
- Data Warehouse is focused on all departments in an organization, whereas Data Mart focuses on a specific group.
- Data Warehouse designing process is complicated, whereas the Data Mart process is easy to design.
- Data Warehouse takes a long time for data handling, whereas Data Mart takes a short time for data handling.
- Comparing Data Warehouse vs Data Mart, Data Warehouse size range is 100 GB to 1 TB+, whereas Data Mart size is less than 100 GB.
- When we differentiate Data Warehouse and Data Mart, the Data Warehouse implementation process takes 1 month to 1 year, whereas Data Mart takes a few months to complete the implementation process.
What is Data Warehouse?
A Data Warehouse collects and manages data from varied sources to provide meaningful business insights.
It is a collection of data which is separate from the operational systems and supports the decision making of the company. In Data Warehouse data is stored from a historical perspective.
The data in the warehouse is extracted from multiple functional units. It is checked, cleansed and then integrated with Data warehouse system. Data warehouse used a very fast computer system having large storage capacity. This tool can answer any complex queries relating data.
What is Data Mart?
A data mart is a simple form of a Data Warehouse. It is focused on a single subject. Data Mart draws data from only a few sources. These sources may be central Data warehouse, internal operational systems, or external data sources.
A Data Mart is an index and extraction system. It is an important subset of a data warehouse. It is subject-oriented, and it is designed to meet the needs of a specific group of users. When compared Data Mart vs Data Warehouse, Data marts are fast and easy to use, as they make use of small amounts of data.
Differences between Data Warehouse and Data Mart
Here is the main difference between Data Mart and Data Warehouse:
|Parameter||Data Warehouse||Data Mart|
|Definition||A Data Warehouse is a large repository of data collected from different organizations or departments within a corporation.||A data mart is an only subtype of a Data Warehouse. It is designed to meet the need of a certain user group.|
|Usage||It helps to take a strategic decision.||It helps to take tactical decisions for the business.|
|Objective||The main objective of Data Warehouse is to provide an integrated environment and coherent picture of the business at a point in time.||A data mart mostly used in a business division at the department level.|
|Designing||The designing process of Data Warehouse is quite difficult.||The designing process of Data Mart is easy.|
|May or may not use in a dimensional model. However, it can feed dimensional models.||It is built focused on a dimensional model using a start schema.|
|Data Handling||Data warehousing includes large area of the corporation which is why it takes a long time to process it.||Data marts are easy to use, design and implement as it can only handle small amounts of data.|
|Focus||Data warehousing is broadly focused all the departments. It is possible that it can even represent the entire company.||Data Mart is subject-oriented, and it is used at a department level.|
|Data type||The data stored inside the Data Warehouse are always detailed when compared with data mart.||Data Marts are built for particular user groups. Therefore, data short and limited.|
|Subject-area||The main objective of Data Warehouse is to provide an integrated environment and coherent picture of the business at a point in time.||Mostly hold only one subject area- for example, Sales figure.|
|Data storing||Designed to store enterprise-wide decision data, not just marketing data.||Dimensional modeling and star schema design employed for optimizing the performance of access layer.|
|Data type||Time variance and non-volatile design are strictly enforced.||Mostly includes consolidation data structures to meet subject area’s query and reporting needs.|
|Data value||Read-Only from the end-users standpoint.||Transaction data regardless of grain fed directly from the Data Warehouse.|
|Scope||Data warehousing is more helpful as it can bring information from any department.||Data mart contains data, of a specific department of a company. There are maybe separate data marts for sales, finance, marketing, etc. Has limited usage|
|Source||In Data Warehouse Data comes from many sources.||In Data Mart data comes from very few sources.|
|Size||The size of the Data Warehouse may range from 100 GB to 1 TB+.||The Size of Data Mart is less than 100 GB.|
|Implementation time||The implementation process of Data Warehouse can be extended from months to years.||The implementation process of Data Mart is restricted to few months.|