What is a data mart in data warehousing?

Asked By: Classie Piriz | Last Updated: 28th March, 2020
Category: technology and computing data storage and warehousing
4.2/5 (237 Views . 26 Votes)
A data mart is a structure / access pattern specific to data warehouse environments, used to retrieve client-facing data. The data mart is a subset of the data warehouse and is usually oriented to a specific business line or team. Data warehouses are designed to access large groups of related records.

Click to see full answer


Correspondingly, what is data mart in data warehouse with example?

A data mart is a subset of a data warehouse oriented to a specific business line. Data marts contain repositories of summarized data collected for analysis on a specific section or unit within an organization, for example, the sales department.

Subsequently, question is, what is data mart and its types? Three basic types of data marts are dependent, independent, and hybrid. Dependent data marts draw data from a central data warehouse that has already been created. Independent data marts, in contrast, are standalone systems built by drawing data directly from operational or external sources of data or both.

Considering this, what is the role of data mart in data warehousing?

A data mart is focused on a single functional area of an organization and contains a subset of data stored in a Data Warehouse. Data Mart helps to enhance user's response time due to a reduction in the volume of data.

What's the difference between a data warehouse and a data mart?

KEY DIFFERENCE 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.

35 Related Question Answers Found

What are the types of data warehouse?

Three main types of Data Warehouses are:
  • Enterprise Data Warehouse: Enterprise Data Warehouse is a centralized warehouse.
  • Operational Data Store:
  • Data Mart:
  • Offline Operational Database:
  • Offline Data Warehouse:
  • Real time Data Warehouse:
  • Integrated Data Warehouse:
  • Four components of Data Warehouses are:

What is data warehouse with example?

A data warehouse essentially combines information from several sources into one comprehensive database. For example, in the business world, a data warehouse might incorporate customer information from a company's point-of-sale systems (the cash registers), its website, its mailing lists and its comment cards.

Is data mart a database?

A data mart is a subject-oriented database that is often a partitioned segment of an enterprise data warehouse. The subset of data held in a data mart typically aligns with a particular business unit like sales, finance, or marketing.

What are the components of data warehouse?

There are 5 main components of a Datawarehouse. 1) Database 2) ETL Tools 3) Meta Data 4) Query Tools 5) DataMarts.

What is data mart and its advantages?


Advantages of using a data mart:
Improves end-user response time by allowing users to have access to the specific type of data they need. A condensed and more focused version of a data warehouse. Each is dedicated to a specific unit or function. Lower cost than implementing a full data warehouse.

What is data mart in SQL?

A data mart is a structure / access pattern specific to data warehouse environments, used to retrieve client-facing data. The data mart is a subset of the data warehouse and is usually oriented to a specific business line or team. Data warehouses are designed to access large groups of related records.

What is the difference between a data lake and a data warehouse?

A data lake is a vast pool of raw data, the purpose for which is not yet defined. A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose. The two types of data storage are often confused, but are much more different than they are alike.

What is meant by data warehousing?

A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process. Subject-Oriented: A data warehouse can be used to analyze a particular subject area. For example, "sales" can be a particular subject.

How do you implement a data mart?

Simply stated, the major steps in implementing a data mart are to design the schema, construct the physical storage, populate the data mart with data from source systems, access it to make informed decisions, and manage it over time.

How do I create a data mart?


To set up the data mart, you use OWB components to:
  1. Create the logical design for the data mart star schema.
  2. Map the logical design to a physical design.
  3. Generate code to create the objects for the data mart.
  4. Create a process flow for populating the data mart.
  5. Execute the process flow to populate the data mart.

What is meant by OLAP?

OLAP (Online Analytical Processing) is the technology behind many Business Intelligence (BI) applications. OLAP is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical calculations, and predictive “what if” scenario (budget, forecast) planning.

What is a data warehouse used for?

Data warehouses are used for analytical purposes and business reporting. Data warehouses typically store historical data by integrating copies of transaction data from disparate sources. Data warehouses can also use real-time data feeds for reports that use the most current, integrated information.

Is data mart normalized or denormalized?

Modern warehouses are mostly denormalized for quicker data querying and read performance, but data marts have no preference between a normalized and denormalized structure because they are focused on a single subject or functional organization area.

What is multidimensional data model?

The multidimensional data model is composed of logical cubes, measures, dimensions, hierarchies, levels, and attributes. The simplicity of the model is inherent because it defines objects that represent real-world business entities.

Why would a company invest in a data mart instead of a data warehouse?


Why would a company invest in a data mart instead of a data warehouse? They are lower cost, easier to implement and use, and faster. Data marts serve a specific department or function, such as finance, marketing, or operations. Since they store smaller amounts of data, they are faster, easierto use, and navigate.

Why data marts are required?

Data marts enable users to retrieve information for single departments or subjects, improving the user response time. Because data marts catalog specific data, they often require less space than enterprise data warehouses, making them easier to search and cheaper to run.

What is data model explain?

A data model refers to the logical inter-relationships and data flow between different data elements involved in the information world. Data models help represent what data is required and what format is to be used for different business processes.