Data Warehouse vs. Database: What's the Difference?

Databases and data warehouses are both tools that organizations use to store, access, and analyze data. But, that's not to say they're exactly the same – or even used for the same purposes.

In this article, you'll explore the differences between data warehouses and databases, their use cases, and how they're each used to solve problems. At the end, you'll also explore flexible, cost-effective courses that can help you develop critical data skills today.

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

Data warehouses and databases both act as data storage and management tools. However, there are a few key differences to acknowledge. First, data warehouses have analytical capabilities. They enable companies to make analytical queries that track and record certain variables for business intelligence. In contrast, a database is a simple collection of data in one place. Databases’ main purpose is to store data securely and allow users to access it easily.

Organizations often need both databases and data warehouses to manage the massive amounts of data they produce daily. For example, a clothing company may use one database to store customer information and another to track website traffic. They can use a data warehouse to compare both databases on a historical scale to reveal insight into consumer trends.

Below, we dive deeper into both data warehouses and databases. Read on to learn more.

What is a data warehouse?

A data warehouse is a large, central location where data is managed and stored for analytical processing. The data is accumulated from various sources and storage locations within an organization. For example, inventory numbers and customer information are likely managed by two different departments. However, both data types can be collected and presented on the same dashboard in a data warehouse. Then, data science professionals analyze the data for patterns and use their findings to help organizations make informed business decisions.

Data warehouse use cases

Data warehouses have many different business applications. Their use cases may depend on the industry they're used in. Here are two examples:

• Health care. A data warehouse may carry patient information that health care professionals can use to understand certain conditions or evaluate treatment methods. For example, a health care data scientist may analyze the information in a data warehouse to determine how often cancer patients over 25 receive chemotherapy rather than radiation treatment and why.

• Marketing. A marketing firm may use a data warehouse to track the success of a campaign or product launch. Dashboards and reports can be created and shared within an organization to gauge performance, sales, and customer service interactions.

Read more: Data Lake vs. Data Warehouse: What’s the Difference?

Data warehouse professionals

People who work with data warehouses in their careers are data science professionals. The list below defines a few examples of careers in this field. Keep in mind that the job titles below can vary slightly from industry to industry.

• Data warehouse analyst. A data warehouse analyst researches and evaluates data from a data warehouse. They use their insights to make recommendations for improving an organization's data storage and reporting methods. They may also collect and visualize their findings to assist with other business processes. Data warehouse analysts in the US earn an average base salary of $97,044 per year [1].

• Business intelligence (BI) analyst. A business intelligence analyst uses data warehouses to develop company-wide and department-wide business insights through data visualization. They build reports, dashboards, and other visual aids using programming languages and data visualization platforms like Python, SQL, and Tableau. Business analysts in the US earn an average base salary of $84,541 per year [2].

Data visualization is the visual representation of information. Charts and diagrams are examples of data visualization methods.

• Data warehouse engineer: A data warehouse engineer builds and manages data warehouse strategies. They might be responsible for setting project scopes, choosing the right software tools, and leading strategic solutions. Data warehouse engineers in the US earn an average base salary of $112,092 per year [3].

What is a database?

A database stores information from a single data source for one particular function of your business. They can process many simple queries (requests for data results) quickly. Databases often record real-time data like e-commerce transactions or updates to a patient's health record. Databases can handle “big data” but can also be as small as an Excel spreadsheet. Big data databases can convert structured and unstructured data into formats that analytics tools can use.

Read more: What is Big Data? A Layperson's Guide

Relational database vs. non-relational database

Relational databases, also called SQL databases, store data in rows and columns like an Excel spreadsheet. Non-relational databases use one of the four storage models (document, key-value stores, graph, and column) for more flexible storage and complex queries.

Want to build your own database? The University of Colorado Boulder's Relational Database Design course offers step-by-step guidance to turn your raw ideas into a relational database. You’ll practice online with real-life cases and get comfortable building one in just 36 hours.

Database use cases

Like data warehouses, databases have many different business applications across many industries. Databases can also be for personal use. Here are a few examples:

• Electronic health record (EHR). In health care, patient information can be inputted into an EHR during their first visit. Then, it's updated during subsequent visits. This information stays secure and confidential on the platform. It updates the time and date of the appointment along with any other relevant symptoms and diagnoses. EHRs also enable clinicians to access them at any time from any facility that shares access permission.

• Consumer recommendations. Online streaming services such as Netflix and Spotify use databases to track the TV shows and songs that are offered, as well as your viewing and listening preferences. This information is stored on NoSQL databases and used to recommend content you might like based on your user history.

Database professionals

People who work with databases in their careers are typically data science professionals. The following list defines a few examples of careers in this field. Remember that the job titles below can vary from industry to industry.

• Database administrator. A database administrator ensures that a database runs efficiently. They create and organize systems to store data like financial information, product specifications, and customer orders. Database administrators also manage permissions so that this data is available to those authorized to access it. Database administrators in the US earn an average base salary of $92,464 [4].

• Database architect. Database architects design and build databases. They create the standard for operating, programming, and securing a database. Their primary goal is to make it easy and efficient for data analysts, data scientists, and engineers to access data. Database architects in the US earn an average base salary of $116,955 [5].

• Data analyst: Data analysts gather, clean, and study data sets to help solve an organization’s problems. Database analysts in the US earn an average base salary of $88,282 per year [6].

What is data cleaning?

The term "data cleaning" refers to removing or repairing corrupt, incomplete, duplicated, or otherwise incorrect data.

Learn more about data engineering with Coursera

Do you want to start a career in database engineering or learn how to use data-based tools in your organization effectively? Consider learning from an industry leader online with one of these two Professional Certificates in data engineering: