What is a Data Mart?

A data mart is a small, specialised store of information that sits within a bigger set of data, such as a data warehouse.

Data marts are designed for a particular group of people in a company, like the sales team or finance department. This unit only carries the specific data that those people need for their work, helping teams quickly access data to find key insights more efficiently than they would using a data warehouse. Aligning a data mart with a specific department like sales or marketing can help save valuable time and improve a business’s overall data management.

Difference between data marts, data warehouses, and data lakes

Data marts, data lakes, and data warehouses are all types of data management. All types have their uses and although they share some similarities, each one is unique.

Here is an overview of each one:

Data warehouse

A data management system that can store structured data from a variety of different sources.
Data is structured which means it’s already been cleaned and formatted into a unified form.
The purpose of the data is typically well-defined.

Data lake

They are centralised repositories containing structured, unstructured and semi-structured data.
Data can be made available right away for real-time analytics, data science and for machine learning.
Data lakes store large amounts of raw data however a data mart and data warehouse requires the data to be structured.

Data mart

A data mart is a simple form of a data warehouse which focuses on a specific area of a business like sales or marketing.
They collect data from fewer sources compared to data warehouses. Data can even come from a central data warehouse.
Other data like external data or internal data can be included in a data mart.

What are the benefits of data marts?

There are multiple benefits to using a data mart which include:

Access data more efficiently: data marts provide teams with easy access to specific data subsets that relate to their roles and responsibilities. Companies can even set up access permissions that only grant teams access to their respective data mart. Once these connections are established, teams can analyse data in real time from the data marts, with no need to depend on IT for periodic data extractions, streamlining operational efficiency.
Quicker insights: a data mart facilitates data analytics at the departmental level which differs from a data warehouse. Analysts can concentrate on addressing specific challenges and finding opportunities through the data resulting in faster business decisions being made.
Centralised data: data marts centralised data, helping ensure everyone involved in the decision-making process within a department or business is able to access the same data. This helps establish trust in the data and any insights or decisions that are made based on it. Stakeholders are able to prioritise decision-making and taking action instead of questioning the integrity of the data itself.
Business scalability: data marts offer a flexible data management system that is aligned with business requirements. This includes the ability to use historical data from past projects to support current tasks. Data can be updated and altered depending on the project it’s being used for making the process fully scalable.
Implement improvements faster: creating a data warehouse that caters to the needs of a whole business or organisation takes a lot of time and planning. A data mart on the other hand focuses on specific teams and areas of a business so it needs less data sets making it far quicker to set up.

What types of data marts are there?

The choice of data mart type carries significant implications for an organisation's data strategy. There are three types of data marts, which include:

Dependent data marts: a data mart populated from a central data repository or data warehouse. They offer data consistency and reliability, ensuring that all units access the same trusted data source. However, if the central repository encounters issues or changes, it can create bottlenecks and disruptions in data access.
Independent: these data marts stand alone, not tethered to a central data warehouse. Teams have their own data mart without dependency on a centralised system. This autonomy helps encourage agility across teams, but necessitates careful data quality and governance to maintain consistency.
Hybrid: these types of data marts blend both dependent and independent data marts. Hybrid data marts enable organisations to maintain some centralised control while allowing select units to operate independently. This equilibrium between data consistency and flexibility is valuable, albeit requiring more intricate management.

Who uses a data mart?

Data marts play a key role in helping businesses make key decisions across the organisation, meaning that any department could use a data mart. Typical users of data marts include:

Business analysts
Data analysts
Data scientists
Departmental managers
Executives and decision-makers
Sales and marketing teams
Finance teams
Operations teams
Customer support teams

A marketing team might utilise data marts to analyse what to identify demographics for products whilst a sales team may use it for regular data reporting. These tasks are carried out within specific departments eliminating the need for broad access to all enterprise data.

A data mart is usually designed and managed by the department within a business that will use it.

Data mart use cases

We created a data mart for a digital solutions client who had a number of different datasets across their organisation and were looking to define and measure KPIs for all their business functions. The client benefited from improved visibility of business performance, helping them better define their targets and track progress through:

Streamlined access to dependable data from a single, readily accessible source
Reduced manual involvement in reporting, minimising the risk of errors
Enhanced awareness of operational problems and their root causes
Resolution of data-related issues affecting performance and operations within systems

We also implemented a data mart for an engineering solutions client that were looking to better service their customers whilst securely managing their data. The client substantially improved their data management, reporting, and analytics capabilities. They can now deliver intricate reports via engaging dashboards, analyse specific trends, and perform root cause analysis thanks to:

Adoption of a modern, centralised data repository for efficient data storage and management
Simplified, faster, and repeatable access to trustworthy data
Enhanced data governance, ensuring consistency in both data and reporting

How to design a data mart

List all the essential requirements needed for the data mart to work effectively for your specific business needs.
Identify which data sources will need adding to your data mart.
Decide what data subset is required and whether all information on a subject is required or if it’s granular level data.
It should have a logical layout with schema that corresponds with the larger data warehouse.

Designing a data mart can be challenging. If you’re looking to streamline business processes with data marts, we can help. Learn more about our data management solutions, or get in touch with us to find out more.

Moving data marts to the cloud

Data marts offer lots of flexibility however they can only store so much data in an on-premises solution. With data warehouses and data lakes moving to the cloud, data marts need to follow too.

A shared cloud-based platform is the most efficient way for everyone in a business or team to access data in real-time. Businesses can reduce costs by consolidating data resources into one repository that includes all their data marts.

Advantages to cloud-based solutions include:

Cloud based applications offer flexible structures
Single depository containing every data mart a business has
Resources accessible anywhere at anytime
More efficient data access
Reduces costs by consolidating data
Real-time data and analytics

Do I need a data mart?

Data marts provide a flexible and scalable solution for managing and analysing data. You should consider a data mart if you wish to:

Improve operational efficiency
Draw clearer business insights and improve visibility of performance
Modernise data management practices for scalability
Gain better control of data assets

If you’re considering implementing a data mart, you can contact our experienced team who will find out what your current business challenges are and offer you tailored solutions.

Frequently asked questions about data marts

What is data silo vs data mart?

A data silo is a standalone data repository or system that stores data independently from other systems. A data mart is a simplified form of a data warehouse that focuses on a single subject or line of business.