Types of Data Mart

There are three common types of data marts:

• Independent Data Mart
• Dependent Data Mart
• Hybrid Data Mart

1. Independent Data Mart

An independent data mart is created and maintained separately from the data warehouse. It is created to satisfy the particular needs of a specific business unit or department. Independent data marts are typically smaller in size and more rapidly and readily set up. They offer flexibility and agility since they are not constrained by the challenges of the centralized data warehouse. Nevertheless, data redundancy and inconsistency may result if it is replicated over several different data marts.

2. Dependent Data Mart

A dependent data mart is generated right out of a data warehouse. It takes some of the data from the data warehouse and arranges it to meet the needs of a specific industry. Dependent data marts, which profit from the data integration, data quality, and consistency provided by the data warehouse, allow for the centralization and preservation of all data in a single source of truth. They are often developed to serve particular reporting and analytical needs, and they are frequently updated from the data warehouse. Dependent data marts offer data consistency and prevent data duplication because they rely on the data warehouse as their main source of data.

3. Hybrid Data Mart

Both independent and dependent data mart components can be found in a hybrid data mart. As well as combining additional data sources particular to a given business unit or department, it makes use of the centralized data warehouse for the integration and consistency of the core data. By offering flexibility and agility for department-specific needs while keeping the integrity and consistency of shared data from the data warehouse, hybrid data marts offer the benefits of both strategies. This strategy creates a balance between localized data management and centralized control.

A data mart is a specialized subset of a data warehouse focused on a specific functional area or department within an organization. It provides a simplified and targeted view of data, addressing specific reporting and analytical needs. Data marts are smaller in scale and scope, typically holding relevant data for a specific group of users, such as sales, marketing, or finance. They are organized around specific subjects, such as sales, customer data, or product information, and are structured, transformed, and optimized for efficient querying and analysis within the domain.