Data Mart vs. Data Warehouse: What are the Differences and Advantages for Each?

Relational Database Management System

Data Mart vs. Data Warehouse: What are the Differences and Advantages for Each?

Both small and big enterprises use data to develop strategies and make better decisions in all areas of their operation. But how do they collect, store, organize, and maintain this data? The data warehouse and data mart are repositories often leveraged to gain valuable insights into the entire enterprise or specific units. The two are similar, but they serve different purposes, and a company can use one or both storage units.

This article walks you through the major differences between the data mart and the data warehouse. It also highlights the advantages of each one of them. Keep reading to understand how you can employ these repositories in your organization.  

Data Mart vs. Data Warehouse: Side by Side Comparison

infographic for Data Mart vs Data Warehouse
Data MartData Warehouse
Aimed at  Departmental levelEnterprise level
Held DataSummarized dataDetailed data
UsageTactical decisionsStrategic decisions
Data SourceLimited ( relevant systems/ applications within a specific department)Multiple ( can be various systems/applications within an organization)
Building DurationWeeks to a few monthsMonths to years
Data SizeLess than 100GBMore than 100GB
DesignBottom-Up ApproachTop-Down Approach
Candidate Key Vs. Primary Key
Both a data mart and a data warehouse use aggregated data to help you make better business decisions.

Data Mart vs. Data Warehouse: What’s the Difference?

Let’s explore in more detail the key differences between these two storage solutions.


Data Mart

Data Mart is a structure that aggregates data from a single or a few sources, such as a data warehouse, external sources, and internal operational systems. This data warehouse subsection focuses on generating meaningful insights for sound decision-making. It focuses on a particular part of a business or agenda.    

In other words, a data mart is a simple and smaller data warehouse type of less than 100 gigabytes. Again, it focuses on a single subject and takes several months to implement. For instance, your sales or finance department may use a data mart to report or analyze their activities. A storekeeper may also utilize a data mart to determine and report commodities flow in their storeroom. In addition, you could use the model to determine your business processes and areas that need improvement.

Data Warehouse

A data warehouse is a centralized unit that collects, stores, analyzes, and consumes large volumes of data from multiple sources. Data extraction, transformation, and loading occur in the initial staging layer.  

That said, the data warehouse supports complex transactional processing, as it is a key component of business intelligence. For instance, the finance department may use account balances, transactions, and endowment data to make sound financial decisions for a firm. In addition, a data warehouse creates an analytic basis, since it links raw information from various data sources. For example, you can use it to analyze product acquisition information and marketing details from their storage systems.

You can also merge several data marts from different organizational units to have a data warehouse. The process is ideal when working with a limited budget and time. Alternatively, consider starting with a data warehouse from which you design data marts for your departments.  

When to Use:

Data Mart

Integrating a data mart into your business data management system will streamline department activities. If well leveraged, the structure can help you gain valuable insights and address organizational problems quickly.

In addition, this platform controls data access and protects it from accidental writes. Hence, designing several data marts is paramount to any business, especially those dealing with sensitive information. That explains why large enterprises have data marts for specific units or subjects, as it helps them restrict data access to specific individuals.  

Beyond this, a data mart provides a centralized unit to store, process, analyze, and report on the departmental level. Thus, departmental teams can easily access their performance metrics and identify specific areas that need improvement. For instance, sales, return on investment, as well as individual and customer reviews.

Are you looking forward to driving company growth through resource allocation? Consider getting a data mart for each department to balance resource distribution across the entity. For instance, the human resource data mart will have facts about your employees, from their qualifications to performance. A shipping data mart will track the total cost and time spent to deliver a product. While an accounting and finance data mart will store financial information. You can optimize this information to develop your business strategically.

Data Warehouse

The data specialists, financial planners, production managers, marketing teams, and chief executive officers use the data warehouse to make well-analyzed decisions for the entire organization. Remember, the data warehouse integrates data from multiple sources; it can be from all department’s online transactional processing systems, among other sources.

When analyzing and deriving reports, the decision-makers will use the data from all department systems to help identify patterns and trends in the business. Thus, the data warehouse will provide all the required insights from finance, sales, human resources, production, and supply chain units. The leading decision-makers will then incorporate the data from various departments into a performance data set and distribute the summarized insights to the higher management for better decision-making.

For a comprehensive analysis, managers can also use the data warehouse to evaluate the performance of each employee by consolidating data from the various relevant departments. For instance, the marketing manager may draw data from the customer care unit, sales department, and human resource system to evaluate the achievements of each sales representative.


Data Mart

There are three main types:

Dependent Data Mart: Building a dependent data mart means you extract data from an established data warehouse.

Independent Data Mart: Unlike a dependent data mart, an independent data mart uses data from internal and external sources. The data mart repository is not linked to a data warehouse and is ideal for smaller business units and short-term business goals. Despite this, managing the stand-alone system becomes difficult for an expanding entity since it requires separate logic and Extraction, Transformation, and data Loading tools.  

Hybrid Data Mart: A hybrid data mart obtains data from both the data warehouse and external sources. It is suitable for database environments with a fast application turnaround.

Data Warehouse

Here are the primary models of the data warehouse:

Enterprise Data Warehouse (EDW): Making decisions for the entire company requires comprehensive data from all departments, and that’s where the enterprise data warehouse comes in. It provides all the needed insights for overall company management. It also provides unified data classification and representation methods.

Operational Data Store (ODS): Maintaining records of routine activities, like the flow of items in a store, requires a solid database system, and the ODS aids in keeping such records. It gets the information from the data warehouse.

Data Mart: It is a small part of the data warehouse structure. As mentioned, a data mart provides vital insights to a specific business line or team. It’s a time-saver tool, as information stored in this repository is department or subject-specific.

Candidate Key Vs. Primary Key
A data warehouse is able to have data marts amongst its architecture components.

Data Mart vs. Data Warehouse: 6 Must-Know Facts

  • Organizational specialists, data designers, and data scientists are the common users of data warehouse structures.
  • A data mart processes low volumes of data for a few people in a particular business unit, while a data warehouse provides numerous datasets for the entire entity.
  • A data warehouse provides a platform for data from various sources.
  • A data mart is among the data warehouse’s architecture components.
  • A data warehouse can have several databases.
  • A data warehouse holds structured, semi-structured, and ad hoc data.

Data Mart vs. Data Warehouse: Which One Is Better? Which One Should You Use?

A company may use both a data mart and a data warehouse or only one of them. A data warehouse is ideal for storing and processing large volumes of data for an enterprise. It provides a perception of the entire organization. Conversely, a data mart holds smaller data volumes. It is a small segment of the data warehouse that aids in providing an overview of the specific divisions that make an enterprise.

Thus, consider a data warehouse if you want to analyze data from disparate sources. However, use a data mart if you are interested in analyzing data for a specific division.

Advantages of a Data Mart

  • Easy Performance Tracking: It stores individualized and specific data for a particular unit or team.
  • Cost Effective: Setting it up is cheaper than a data warehouse as it requires fewer resources.
  • Shorter implementation time: The construction process is shorter than that of a data warehouse.
  • Improved End-User Experience: This repository holds data for a particular department, giving you a great end-user experience as data is available on request.
  • Enhances Research: Finding supporting facts and statistics about a particular line of business is easy and effective.
  • Data Protection: It allows for separate data storage mechanisms to secure information, lowering the risks associated with hacking.
  • Efficient Data Retrieval: It stores specific information, thus allowing fast data retrieval.

Advantages of a Data Warehouse

  • Comprehensive Business Intelligence: This data storage structure leverages the organization’s analytics, supporting data integration. In return, it improves your business intelligence. For instance, cross-checking multiple databases for product information can be inconvenient and time-consuming. But a data warehouse provides relevant and timely details about business marketing.
  • Enhances Data Quality: A data warehouse ensures your business policies are based on refined data from multiple sources. By mastering the data warehouse model, you can align data and remove obsolete and replicated details from the information. As a result, you’ll have access to high-quality data when making organizational plans.
  • Holds Historical Data: This data aids in making strategic decisions and predicting your business’s future. For instance, the sales team uses historical data to plan promotional campaigns and determine marketing strategies for upcoming promotions.
  • Enhance Data Security: Your business will not require additional data security when using a data warehouse. The platform has features to protect customers, staff, and general business information.

Please note that both a data mart and a data warehouse play a significant role in decision-making and promoting best business practices. As mentioned above, the data mart is crucial to a department or several units in a small establishment. In contrast, the data warehouse covers an entire organization and is recommended for use in large enterprises.

Frequently Asked Questions

Why is a data warehouse said to be subject-oriented, and what does this mean?

A data warehouse is made to serve a specific purpose. It could be gaining insights on particular topics (the subject) like inventory, sales, revenue, customer satisfaction rate, etc. For example, a sales data warehouse will provide insights to any department interested in understanding the business’s marketing and sales activities.

How do I get started with a data mart?

Start the data mart creation process by opening the premium workspace. Select + New followed by ** Data mart and proceed with data loading.

Can I alter the data in a data warehouse?

The data warehouse is non-volatile, meaning the data stored in this structure remains intact. Any altered information is stored in a separate chamber. This helps in understanding when and how historical data changes happened.

Which type of data does a data mart store?

A data mart stores data that aligns with specific business lines such as finance, marketing, or research-related data.

Does a data mart have layers?

An architected data mart has virtualization, business transformation, and reporting layers.

Does the data warehouse support integration of data?

The data warehouse integrates data from various sources into a common format for further analysis.

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