When companies are figuring out how to store their data, one of the questions that arise is whether a data warehouse is necessary.
Unfortunately, many people who aren't IT professionals may not even know what a data warehouse is, or how it differs from a database software. Read on to learn more about databases and data warehouses, and how to determine what meets a company's needs.
Data Warehouses vs. Database
A database is a collection of organized data. For instance, a database may group all information about customers (such as name, age, gender and so forth) or transactions (such as date placed, amount, items purchased and so on).
Databases are designed so the data they hold is easy to read, write, search and delete. Databases are usually linked to one particular program, which serves as a front-end that helps employees access and modify data. Accessing and editing data within a database should be virtually instantaneous. Databases can hold huge amounts of data that is easily modified, such as the Pokemon Go database.
While anything from a .txt file to an Excel spreadsheet can be a database, one of the most common database formats is an online transaction processing (OLTP) application file. A good database will have near-constant uptime, because when a database is down, this can seriously affect a company's operations.
While databases are extremely useful, due to how they're commonly constructed, it's often very difficult for a database administrator to write a program that will perform analytics on the data a database contains. Most reports run will be static, one-time reports (such as a PDF), rather than dynamic. For reports and analysis, it's more useful to turn to data warehouses.
Data warehouses are a special type of database, specifically constructed with an eye toward running analytics. While most databases are OLTP application files, most data warehouses are online application processing (OLAP) files. OLAP gets information by gathering data from OLTP and other database files. Because of how OLAP files are structured, it's far easier to run queries and analyses on the data they contain, and anyone can query the data warehouse with either data warehouse software or knowledge of SQL. Individual subsections of the data warehouse, which are typically relevant to an individual team or department, are called "data marts."
While databases are expected to have 99.99 percent uptime, data warehouses usually don't need to have that kind of uptime. Although the analyses people perform with data warehouses are vital to companies' operations, data warehouses aren't constantly being read and written to like databases are. Most data warehouses will refresh themselves with data from databases, often every 24 hours or so.
Good data warehouse analyses, and good software, help businesses discover the story behind data. They let businesses know what's really happening, and they help businesses plan for the future.
Which Is Better?
Databases aren't better than data warehouses, or vice versa. They perform very different functions from one another, and each is very powerful.
Most companies that handle digital data will need at least one database. Small companies, or new companies, may be able to do without data warehouses for a time. But once the need for analytics arises, a data warehouse is invaluable.
By educating themselves about and implementing data warehouses, companies' IT departments can make running even complicated analyses very simple. Databases are powerful tools, but once companies implement a data warehouse, they'll wonder how they got along without it.