A Data Mart is a data warehouse designed to serve a specific line of business, industry, team, or task. Unlike a data warehouse, Data Mart stores homogeneous data. The showcase allows you to provide highly relevant data to certain groups of users, which contributes to quick decision-making.
Components of data marts
The initial data. The data that the data showcase is based on. They are often extracted from a variety of sources, including operating systems, external data sources, and data warehouses.
Setting up the data. The process of preparing data for use in storefronts. It includes data extraction, transformation, and loading (ETL) operations.
Keeping. The place where the converted data is stored for future use. The storage component includes a data model that defines how data is structured and organized.
Access tools. Tools and applications that end users use to query and analyze data in data marts.
Advantages of Data Marts
Efficiency. Data marts often provide higher query performance.
Relevance. Data marts provide end users with up-to-date data, as they focus on a specific area of business.
Flexibility. Data marts can be created and modified faster than data warehouses. This way they can respond more flexibly to changing business needs.
Differences between data marts and data warehouses
Data marts and data warehouses differ in their scope and purpose.
Scope of application. The data warehouse stores a huge amount of data from across the organization, while the data showcase focuses on a specific area of the business.
Users. The data warehouse caters to a wide range of users and use cases, while the data marts are targeted at a specific user group or department.
Complexity. Creating and managing a data warehouse is usually more complicated and time-consuming than managing data marts.