Business Intelligence and CRM applications are able to extract the information they need from the company’s production files. However, the data is often in different formats and, above all, they are not easily exploitable because they are codified or incomplete. So we create data warehouses.
Difference between Data warehouse and Data mart
We’ll draw a comparison between data warehouse and data mart on the basis of what they are and to what extent they’re beneficial in managing/storing data.
Data Warehouse is an intermediary storage location for the various data in order to build the decision-making information system. It is a warehouse in which an extremely large volume of consolidated data is centralized from the various sources and information of an enterprise.
Simply put, it is a repository of information collected from multiple sources, stored in a unified schema, on a single site allowing the integration of various application systems. Once this data is collected, they are stored for a long time, therefore have a long life and provide access to historical information.
Data warehouse provides the user with a single integrated data interface that allows the user to easily write decision support queries. Data warehouse helps turn data into information. The design of a Data warehouse includes a top to down approach.
It gathers information on topics covering the entire organization, such as customers, sales, assets and items. Therefore, its range covers the entire company. In general, the constellation schema of facts is used, which covers a wide variety of topics. A Data warehouse is not a static structure and evolves continuously.
Check below how one of the tech giants, Microsoft provides data warehouse solutions:
A foundation for enterprise analytics. From SQL queries to machine learning and AI. Take a close look at Azure’s Modern Data Warehouse solution pattern. https://t.co/9xcOj7ip89 pic.twitter.com/smHGUkGxhT
— Microsoft Mechanics (@MSFTMechanics) June 19, 2019
- Timely access to data.
- Removes the loading of information, processing from transactional databases.
- Data warehouse data is non-volatile containing historical data as well as current.
- Data Warehouse delivers enhanced business intelligence.
- Enhances data quality and consistency.
- Increases productivity of corporate decision-makers.
Data mart can be called as a subset of a data warehouse that corresponds to a certain set of users. Data warehouse involves multiple logical data marts that must be persistent in their data artwork to ensure the robustness of a data warehouse. A data mart is a set of tables that focuses on a single task and are designed with a bottom-up approach.
Data mart brings together a set of aggregated, organized, and targeted data for the sole purpose of meeting the needs of the trades. In the technical sense, it is created from a relational database exploited from the SQL computer language and stored physically on a hard disk through a database management system. It is located downstream of the data warehouse and is powered by it.
- Extended development
- Works to integrate all data sources
- Contains only essential business information and data and is less cluttered
- Easy understanding of data
- Improved reporting performance due to smaller queries
- Improves end-user response time by allowing users to have access to the specific type of data they need
Key Differences between the Two
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