All You Need To Know About Data Warehouse Architecture

Updated 3 March 2023

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.

Data warehouse architecture is a system for storing and accessing information that companies use. Data warehousing functions to provide a centralised location for all company information, organising and cleaning it for optimal use. If you are interested in a data warehousing-related career, learning more about what they are and how they work can be beneficial. In this article, we explain what data warehouse architecture is, describe the three layers of this architecture, explore the three types of data warehousing, provide potential careers and share a few helpful tips for finding a job in this field.

What is data warehouse architecture?

Data warehouse architecture is a system that allows companies and organisations to store their data in a single place. It allows companies to simplify their data storage, eliminate errors and reduce redundancies. Here are some important aspects of it:

Subject-oriented: Data warehouse architecture is subject-oriented because it allows companies to store specific data within the warehouse. For example, a company may store their marketing data within their warehouse, but not their payroll information.
Integrated: Data warehouse architecture integrates throughout an organisation by offering accessibility from various points. The integration provides consistency in naming procedures, organisation and formatting throughout the data storage.
Time-variant: Warehouse architecture is time-variant because it includes the moment of observation for each piece of data. It allows the system to recognise each piece of data within a specific period and provides information from a historical perspective.
Nonvolatile: This aspect of data architecture means that previous entries of data remain when new entries occur. This allows companies to avoid losing important information.
Summarised: By summarising data, the architecture can increase speed and performance in query performance. It continuously updates as users include new information.

What are the three layers of data warehouse architecture?

These are the three layers within data warehouse architecture:

Single-tier

The single-tier method for data warehousing contains only one stratum for data storage. Companies do not use this architecture very often, as it is not as complex and expansive as other options. The single-tier approach can reduce data redundancy, but does not feature the benefits of other approaches.

Double-tier

The double-tier architecture uses two layers within its structure. This allows the database to separate data and data sources, but it may be difficult to expand the storage within this system. Because of its design, it may also experience frequent connectivity issues.

Triple-tier

This is the most common form of data warehouse architecture and has three layers, including bottom, middle and top. Triple-tier architecture's bottom layer is the relational system where users input information. Within the middle section, you can find structure to clean and organise information, and it is between the input and the user-end. The top portion is the client's end, where they can gather and use the data within the warehouse.

What are the three types of data warehousing?

These are the three forms of data warehousing:

Enterprise data warehouse: Enterprise data warehousing is a type of data warehousing that large companies may choose to use. It centralises information and data for an entire business network.
Operational data store: This type of data warehousing is a smaller system. It can serve as a data source for the enterprise system because it contains less information and does not centralise access for everyone in the business.
Data mart warehouse: The data mart warehouse is a subset of an enterprise system or operational data store as well. It can include very specific information from a company, like sales or inventory.

8 careers in data warehouse architecture

If you are interested in working with data warehouses, many industries use data warehousing and create roles for those who can create and use them. These industries include manufacturing, healthcare, hospitality, insurance, finance and banking. These are some positions that may work with data warehouses:

1. Support specialist

National average salary: ₹15,137 per month

Primary duties: Data support specialists work with private companies and organisations to improve their data storage and security. When companies face data breaches, support specialists minimise the damage and prepare a defence to reduce legal risk. They can offer support to professionals within the company to recover compromised data as well.

2. Marketing analyst

National average salary: ₹18,212 per month

Primary duties: A marketing analyst may use data warehouses to gather and analyse data about current or potential trends. They can gather and assess data from competitors to determine the best marketing decisions, or evaluate their own marketing data to predict their consumers. Marketing analysts advise company officials and product developers about which products their consumers may want and how the pricing structure can best function.

3. Data analyst

National average salary: ₹31,446 per month

Primary duties: A data analyst is a professional who uses a company, industry or organisation's information to determine the best course of action for a department or organisation. They collect information by identifying the most actionable and accurate methods for finding data, then refine that information by only including what is most relevant. Data analysts interpret the data by applying it to business situations and recommending action depending on current or future trends.

4. Business analyst

National average salary: ₹42,298 per month

Primary duties: Business analysts focus on informing business or company information by using complex systems of data. They can use this data to recommend action like a data analyst, but they may also use the information to improve current processes and make the organisation more efficient. For example, a business analyst may suggest changes to the supply chain management process to reduce waste and increase profit. They may also advise administrators when making substantial business decisions.

5. Database administrator

National average salary: ₹6,61,231 per year

Primary duties: Database administrators are computer science professionals who specialise in creating and managing software to store, clean and organise data. For companies, they can design and maintain systems for financial information, client data, shipping dates and other important details. Through management and performance monitoring, database administrators ensure that each data warehouse functions properly and efficiently.

6. Security analyst

National average salary: ₹8,34,241 per year

Primary duties: While a support specialist prepares a company for potential data breaches, the security analyst works to prevent these events. They monitor data and use access points for suspicious behaviour. A security analyst also implements security software and network infrastructures that protect sensitive data.

7. Cloud engineer

National average salary: ₹9,54,690 per year

Primary duties: Cloud engineers are computer and data specialists who maintain and manage data storage and accessibility through the internet. They may improve cloud security and seek ways to optimise performance. A cloud engineer can work for a company to manage their cloud data or work with a cloud storage provider. For example, some companies offer cloud storage to their clients, and cloud engineers ensure this data is secure and stable.

8. Data engineer

National average salary: ₹10,56,795 per year

Primary duties: Data engineers are also professionals who work with data, but they design the systems that manage and store data. They can review data systems and identify which areas need improvement or solve performance issues. The engineer may also upgrade and update data systems for companies and organisations.

Tips for finding a job in data warehouse architecture

You can use these helpful tips for finding a job in data warehouse architecture:

Obtain a bachelor's degree in computer science. Though you may not be required to have a computer science degree for some positions in data warehousing, having one can improve your chances of finding employment and offer you opportunities for better positions.
Gain relevant server and coding experience. When working with data and databases, you often need to have experience in other areas of computer science. Understanding server fundamentals and how to code can improve your resume and increase your job offers.
Develop your warehousing techniques. Gaining knowledge in data and data warehousing methods can allow you to improve your chances of finding a position that uses them. You might develop techniques for improving the system itself or for using it advantageously.
Build skills in other software and programs. If you are interested in a position that includes leadership or management, it can be helpful to understand other software and programs like word processors and spreadsheets. Developing a thorough skill set for various computer applications can elevate your employee profile and value.
Review company information before applying. Reviewing company information and the job listing before applying for a position can allow you to create application materials that highlight your most relevant skills. By reviewing company information, you can also ensure the workplace environment and company philosophies align with your own.

Salary figures reflect data listed on Indeed Salaries at time of writing. Salaries may vary depending on the hiring organisation and a candidate's experience, academic background and location.