What is a data warehouse? (Plus the benefits of using one)

By Indeed Editorial Team

Published 25 April 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Many companies use significant amounts of data for their work, which they're then required to access and search regularly. Businesses usually require data management systems to make this process more straightforward. One way to manage data is data warehousing, which helps businesses collect and analyse data to support decision-making. In this article, we answer the question 'What is a data warehouse?', outline their architecture and design, name some jobs that work with data warehouses and discuss the benefits of using a data warehouse for business purposes.

What is a data warehouse?

The answer to the question, 'What is a data warehouse?' is that it's a data management system that businesses can use for storing large amounts of data in a single system. It supports business intelligence activities, particularly analytics. Data warehouses contain data that derives from multiple different sources and perform analysis and queries on this data. This might include extensive historical data. Businesses use the data warehouse's analytics to support and improve decision-making that requires specific business intelligence. Data warehouses can be useful for:

  • analysing customer markets

  • developing new product strategies

  • analysing business operations

The architecture of a data warehouse

Data warehouses can have a variety of different architectures. This typically depends on the specific requirements of the business. A company might use a customised solution, but there are some types of architecture that organisations commonly use for data warehouses. These are the types of architecture you are most likely to encounter:


Simple architecture is a basic design that all data warehouses have. Simple architectures store all data in a central repository. The repository receives new data, and users can access data from the repository for analysis, queries and data mining.

Related: What is a database query? (Plus methods and types)

Simple with a staging area

Another common type of data warehouse architecture is the simple with a staging area form. This is another type of simple architecture, but it includes a staging area that processes data before it's added to the central repository. The purpose of this is to simplify data preparation and make it more efficient.

Hub and spoke

Hub and spoke architecture have various data marts extending from the central repository. This architecture allows organisations to better customise the data warehouse to suit the requirements or different areas of the business. When data is ready for use, it moves to the relevant data mart, making accessible data more relevant for end-users.


Sandboxes are private and secure areas within a data warehouse. Companies use sandboxes to informally look at new data sets or experiment with new data analysis methods. Sandboxes are necessary for this type of work because analysis usually has to comply with the protocols and rules of the data warehouse. Using a sandbox means end-users can work outside of these rules and experiment.

Designing a data warehouse

Careful work is necessary when designing a data warehouse to ensure that it meets the requirements of the organisation. Before designing a data warehouse, it's crucial that organisations are certain about their requirements and the scope of their work. Try to consider the end-users within the organisation and what they require from the data warehouse. It's also important to ensure that the data warehouse design can evolve as user requirements change.

When designing a data warehouse, it's important to consider both its logical and physical design. Physical design relates to how the data is physically stored, and logical design refers to how objects within the data warehouse interact. It's also essential to plan processes for data back-up, recovery and transportation. It's vital that data warehouse designs include plans for:

  • specific data content

  • relationships between sets of data

  • the systems environment that supports the data warehouse

  • the types of data transformations that happen

  • the frequency of data refreshes

Professionals who work with data warehouses

A wide variety of professionals work with data warehouses because they're useful tools for organisations in a diverse range of industries and business areas. Data warehouses can serve a variety of different purposes, which means they're valuable across multiple professions. Such professions include:

Data warehouse specialists

Data warehouse specialists work closely with data warehouses and are instrumental in building and maintaining them. They work with businesses to design and implement appropriate data warehouses that meet the individual demands of the business. These professionals are very skilled at building data warehouses for a range of different purposes.


Decision-makers in any area of business are likely to work with data warehouses. They use data warehouses to analyse data that can support key decision making. These professionals, in particular, might work with hub and spoke data warehouse architecture, especially if decision-makers in multiple business areas are using the same data warehouse to support their work.

Sales and marketing specialists

Sales and marketing professionals can use data warehouses to support their work in various ways. Analysing data about conversions, budgets and campaigns can help measure success and efficiency. These professionals can then use this analysis to develop improved campaigns and new strategies.

Related: Marketing department roles and their responsibilities

Benefits of using a data warehouse

There are multiple benefits for organisations if they use a data warehouse. These benefits apply regardless of the nature of the organisation. These are some of the key reasons why businesses choose to use data warehousing for analytics and decision making:

Saves time

It's often necessary to make decisions quickly in business, and using a data warehouse for analytics can save valuable time. Data warehouses allow businesses to access essential data quickly without relying on a technical expert to retrieve it. This means it's easier for businesses to make fast decisions based on data at any time, improving efficiency.

Improves data quality

Using a data warehouse can improve the quality of an organisation's data because the data warehouse properly refines and processes data before end-users can access it. This includes removing inaccurate or duplicate data. Having the data warehouse eliminate data issues helps the organisation operate more efficiently.

Offers convenience

A data warehouse offers businesses convenience, especially if it's using data on a range of subjects or business areas. Data warehouses can perform queries and analyses on specific subjects or business areas. This allows organisations to conveniently and efficiently access the most relevant data to a particular query or challenge.

Improves business intelligence

Using a data warehouse can improve the quality of business intelligence because it consolidates data from multiple different sources. This gives staff a comprehensive understanding of all relevant data and reduces the necessity to gather data from multiple sources. Cross-referencing data from different sources can be time-consuming, complex and challenging to manage. Data warehouses eliminate this issue and improve the quality and availability of business intelligence.

Related: What is business intelligence? (Definition, tools and FAQs)

Creates standardisation and consistency

Data warehouses can make business intelligence data more consistent and help it meet standard rules and protocols. Data warehouses synchronise data from multiple sources. This boosts its quality and gives end-users the confidence that the data is full and accurate, supporting more appropriate decision making.

Increases return on investment

While data warehouses require an initial investment to build and implement, they present businesses with an increased return on investment. The data warehouse enhances the organisation's ability to use its data effectively. This can improve business strategies and help to generate increased sales and revenues. The effectiveness of data warehouses means that organisations can often recover the expense of setting them up fairly quickly.

Related: What is ROI and how to calculate it (examples and formulas)

Stores historical data

Storing large volumes of historical data can present a challenge for businesses, but using a data warehouse makes it easier to store extensive historical data. Past data can be valuable for analysis and making effective decisions. Historical data helps a business understand past successes and helps it identify how to use these strategies again. It can make it easier for businesses to create accurate forecasts and predictions, which can also significantly influence current business strategies.

Boosts data security

Data security is paramount for businesses, and using a data warehouse can help to boost data security. A data warehouse consolidates data in one place and protects it, reducing the risk of a data breach. The integrated security features also mean it's not necessary for businesses to organise additional data security measures. Data breaches can reduce trust in the business and might lose customers, so having rigorous security features can help build customer trust and retention.

Creates data stability

Data within a data warehouse is stable and has been fully processed. When a data warehouse consolidates data from multiple sources, all the data benefits from increased stability. This reduces the risk of data in one source or storage location becoming corrupted or unusable.

Explore more articles