To run a business effectively, your data can’t be a mess.
The “my room isn’t messy; I know exactly where everything is” excuse doesn’t cut it. As your business grows, you’ll collect more and more data. The more data you have, the harder it is to function without organized data.
How do you keep all of your data in order? Welcome to databases 101.
What is a database?Databases, at their core, are pretty simple.
A database is an organized collection of data, stored and retrieved electronically from a computer or server. Databases are distinguished by the types of data they store and the schema used to manage that data.
The method of organization may vary by purpose, data type or other factors, but at their core, all databases consolidate data into a single digital location. Database software, sometimes referred to as database management systems (DBMS), helps users manage the databases they make, enables the creation of new databases, and allows users to easily access data .
A good non-digital example of a database is a phone book. Phone books are used to organize data (names, addresses and phone numbers) by using a unique identifying characteristic — a person’s name — to align data. To find information, you search the phone book by that unique identifying characteristic (referred to in databases as a key value) to retrieve its matching information.
Databases function in much the same way. By storing data using a defined schema, or logical architecture, users can store, modify, search for and retrieve data by following that schema. Some databases require more expertise than others to use, which is important to keep in mind when searching for a database option.
Who uses databases?
What sets databases apart from other IT infrastructure offerings is the universal value they bring to a company. While most IT infrastructure software is only useful to a certain team(s) in an organization, databases can be used by any team that needs to use data.
Typically, a company has a database administrator (or database admin team) that creates and maintains the health — data quality and overall functionality — of the company’s databases. They can also determine which employees can access the data in each database.
From there, depending on what type of data is being stored, anyone in a company can benefit from database access. Here are a few examples:
- E-commerce teams can track transaction data.
- Diagnostic imaging teams for health care providers can access patient information prior to the patient imaging process.
- Suppliers — from the warehouse floor to the management office — can keep a tight watch on incoming and outgoing orders and product inventory with a database.
- IT support teams can use databases to follow changes made to data or systems as a part of the troubleshooting process.
Types of databases
There are plenty of choices when it comes to the type of database a business might want to implement. Each has its own benefits that help it serve a specific function. The core use, though, of databases is to store vast amounts of data in a way that can easily be queried.
This is the type that probably comes to mind first when someone says “database.” Relational databases rely on a spreadsheet-like data structure, but are far more powerful than standard spreadsheets.
Each row contains a primary key, which uniquely identifies the row in the table. The intersection of row and column is a piece of data related to that unique identifier. The rows and columns come together to form a table. Databases can be composed of potentially hundreds of tables.
The data in relational databases is often accessed with a database querying language called SQL (Structured Query Language). SQL does have a learning curve, which has drawn criticism from a usability perspective. Once the language is learned, though, SQL enables users to create highly customizable, complex queries to find the exact data needed.
Relational databases are advantageous for data sets where new tables or data values will be added continuously. Because additions don’t require editing existing data, more data can be added without compromising current data stores.
While relational databases have historically come in one major flavor (structured SQL) and variants thereof, non-relational databases, often referred to as NoSQL databases, tend to offer greater flexibility because they aren’t limited to creating relationships between multiple data points that have the same data structures. Data stored in NoSQL databases does not have to be structured in order to be stored; instead, the organization for the data is provided in how that data is stored. They also can be specialize towards a certain data type(s), such as XML databases (listed below).
As you might suspect, non-relational databases got the “NoSQL” name for not relying purely on rigid relational structures and the requirement to use an SQL or an SQL-esque language to query data.
Document databases rely on document structures to store related data in a semi-structured way. The semi-structuring allows metadata to be stored within the document.
XML databases, as the name suggests, are document databases focused specifically on the storage and retrieval of XML-formatted documents. While XML is used to store document data with markup tags and visible metadata, it’s also human-readable: You don’t need specific expertise to read XML documents. This makes XML databases more user-friendly.
Graph databases enable data storage and retrieval based on graph theory. Data points, referred to as nodes, are connected by a relationship known as an edge. Storing data involves turning that data into nodes and creating edges between nodes. Retrieving the data requires following edges to the related nodes.
RDF databases, or “triplestores,” store and enable retrieval of data using the idea of a triple. A triple is a subject-predicate-object relationship (for example, “Jane knows John” or “red is color”). Data is stored in a triple form, and data retrieval is focused on returning the entire triple relationship.
Key-value stores, the least structured of NoSQL databases, enable storage and retrieval of data by associating a data point to a key value. Data is retrieved by calling a key, and no query language knowledge is necessary for using key-value stores.
Object-oriented databases store data as objects created in object-oriented programming languages such as Java, Python, C++ and Ruby. Because of the nature of data objects, object-oriented databases tend to be used to hold more complex data.
Depending on your business' needs, any of these databases could be the right choice. In fact, the larger a business gets, the more likely it becomes that more than one type of database would be used, and that's okay. For organizing a company's data in meaningful ways, databases are the way to go.
Want to try databases out for yourself? Check out the best free database software.