What is an Analytical Database?
An analytical database is a read-only storage that collects historical data related to operations’ KPIs and metrics such as sales, performance, and inventory.
For organizations, it creates an easily accessible system for any applicable employee or stakeholder to find relevant data, perform queries, and create reports based on the existing data.
While it doesn’t work the same way as a real-time database, it is constantly updated as new data is collected from an organizations’ pertinent data streams.
Analytical databases are built for business intelligence and big data analytics, and usually function as part of larger data warehouses. They are popular because they offer faster query times, simpler maintenance, and easier scalability due to their less volatile nature.
Analytical databases are different from transactional (or OTL) databases which handle transaction processing and other operational applications.
It’s important to remember that the term analytical database can refer to a variety of different database styles.
This includes columnar databases which organize data in columns to reduce the number of data points to be processed; data warehouse applications which include databasing tools in a single platform; in-memory databases which use system memory to expedite processing; MPP databases which use multiple server clusters operating simultaneously; and online analytical processing databases which keep data cubes which can be analyzed based on multiple parameters.
What can I use Analytical Databases for?
One of the primary use cases for an analytical database is to create a faster query system for organizations.
The expanding importance of data, as well as the sheer amount that is produced by organizations daily, means that simply analyzing data as it enters a warehouse can be inefficient and wasteful.
Instead, structured databases within existing warehouses or as standalone applications make data more accessible and easier to interact with by any member of a company.
Perhaps the most common use of analytical databases is to perform broader, more comprehensive analytics than transactional databases can provide.
Whereas transactional databases focus on day-to-day performance and operations, using an analytical database for querying lets you ask “what if” and make predictive analyses more effectively while offering a greater ability to find useful insights from historic data.
Most importantly, analytical databases are a convenient way to give every stakeholder in your organization easy access to data for self-service analytics and specific queries.
