Final answer:
Data marts are usually smaller, quicker to implement, and cost less than data warehouses. They are designed to meet the needs of specific user groups, leading to faster query response times and better alignment with departmental functions.
Step-by-step explanation:
When comparing the advantages of a data mart over a data warehouse, several key points can be highlighted. A data mart is a subset of a data warehouse and is designed to serve the specific needs of a particular department or group of users within an organization. This specificity means that data marts are generally smaller in size, easier to manage, and more tailored to the specific analytical needs of a user group, leading to faster query response times. Additionally, they are often quicker to implement and less costly than establishing a full-scale data warehouse. This is because a data mart only contains relevant data, thereby reducing the complexity and volume of data to be managed.
While both tables and groupings might be used within the context of data warehouses and data marts, the concept doesn't apply directly to the question about their advantages. However, grouping data within these structures can be strategic; for example, organizing data in a data mart that aligns with departmental functions might lead to improved efficiency compared to a data warehouse's broader-structured groups.
The advantages of data marts are particularly observed when end users do not require access to the full breadth of data within an enterprise, but rather need quick access to information that is most relevant to their specific tasks.