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.
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. Data marts are fast and easy to use, as they make use of small amounts of data.
|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.|
- 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.
- Data Warehouse size range is 100 GB to 1 TB+ whereas Data Mart size is less than 100 GB.
- Data Warehouse implementation process takes 1 month to 1 year whereas Data Mart takes a few months to complete the implementation process.