What Is a Database?

Every day we talk about the importance of data—how data is accessed, collected, managed, tracked, monitored, and stored electronically. Databases have quickly evolved. Today, when we are talking about a lot of data, we are literally talking about how businesses are capturing value. They are using this data to track our every movement, in the way we live, work, and play. We are infusing all this information to interpret everything we do and the way we do it.

Managing all this information has become so vital to running daily business that it is rapidly transforming our products and services. Keeping pace with one’s ability and understanding the power of this data is truly what digitization is all about. And having the ability to capture and manage all this information is no easy task.

And it’s just the beginning. Every day another business is discovering how crucial data is to provide a competitive advantage and the need to run a business safely at every level. It is no wonder that we also have more stories of the growing data demands and the intense pressure to manage, track, and securely monitor all this rapidly rising data. Perhaps one of the biggest challenges is to have the right information at our fingertips when and where we need it.

The demands for data tracking and measuring were not always like this. Let’s take a step back in time. In the late 1980s, for instance, relational databases were the dominant database of choice to address many of the data challenges for storing and managing all the structured data.

Today we use database software to address many of these challenges. In those early years, which wasn’t necessarily the case. Back then databases were primarily RDBMS (relational database management systems) used for storing data in a structured format using tables, rows, and columns.

Some of the RDBMS leaders might sound very familiar. Leaders like Oracle, IBM, DB2, (now part of IBM), Sybase, (SAP), and launching in 1989, Microsoft SQL Server. These databases stored data in a structured format using tables with rows and columns, and they employed SQL (structured query language) as the standard language for querying and manipulating data.

To get to the heart of the matter, a database is a scheme of storing data. That’s right when we first started talking about the value of databases. We were talking about them using the simple acronym RDBMS.

Some of the most notable databases serving various purposes:

Types of Databases:

1.        Relational Databases: A relational database defines relationships using tables. Each table contains rows (also known as records) and columns (fields). Consider a customer table with columns that include a name, address, phone number, and even credit line. Each row represents a unique customer entity.

2.     Distributed Databases: A distributed nature of a database enables information to be redundantly stored, partitioned, replicated, or distributed across multiple nodes or servers in which storage devices are not all attached to a common processor offering greater scalability and performance. The information can be stored in multiple computers, located in the same physical location, or spread out over a network of interconnected computers.

3.        Object-Oriented Databases: These databases store data as objects. They are useful for complex data structures, combining data structures with behavior (methods). They were designed to manage complex data types and relationships more effectively than relational databases. They were not widely used as relational databases in the late 1980s.

4.      Centralized Databases: Provide a single central location for users from various backgrounds. These databases are commonly used in large enterprises. Today we have more databases.

Why are databases important? Databases play a pivotal role in our digital age as more and more devices and machines have more information about what is happening as well as the needs of today’s customers. And many of today’s databases serve as the heart of most online services we use daily, including social media sites, banking systems, streaming platforms, and the like.

The complex programs run the gamut, and there are many to choose from for both r the novice user, (such as myself) someone running Microsoft Access, to exceptionally large, sophisticated enterprise systems like Microsoft SQL Server, Oracle Database, and MySQL; just a to name a few. As time has passed, we have gone from on-premises to cloud-based tools. And the likes of AWS, Google, and Microsoft.

For now, the discussion is on understanding that basic databases consist of tables, which comprise of basic grids. It’s important to understand a table can contain data about one piece of information. The well-defined databases model real-world examples.

What that means is they can create digital representations. If we were to create a customer example, clients would be given tables, with a name, address, phone, and credit line all in their own column or otherwise known as fields. One row in the table is for each entity. For instance, in a customer table, there is a row for each customer. This is replicated in other tables.

The other fields are used to identify a row that is unique from another row. Again, as noted earlier, the name is the unique field. For instance, there is only one Alex. If there were two Alex’s, we would have insight into which one owns both orders in the order tables. Now, of course, if we were making a case in our real-world scenario, we would have several customers by the same name Alex A, B, and C with similar names. In this scenario we would use the name and address to make sure we didn’t mix them up. Keep in mind, if they lived at the same address, we would need another field to distinguish between both customers.

To make sure to differentiate between the two Alex’s, in the database, it is quite common to assign customer numbers. In this case, we can make sure the database software will not assign two numbers that are the same. This will enable us to find another Alex or a customer number on some other table, if will reference to one specific customer. There will be no confusion. In the database world it is otherwise referred to as referential integrity.

Walking through the customer numbers and fields truly makes it easier to understand how the data in the various tables relate to one another. In this scenario we see that the fields applied to connect information from one table to the other are simple keys. Traditionally, the order number field is the key that is applied to bridge the order table with order item table to ascertain which items are assigned to which table.

It was not uncommon for many software programs to manipulate the information in a database by applying programming language. SQL (structured query language) was created as a straightforward way to extract data from a database, which really is just another way to query a database.

In the beginning with SQL, you were able extract information from your database. You were able to query the database. Taking SQL a step further, you could get real answers you were able to get answers to questions. Perhaps you want to know more than just the customer’s name, address, zip code. You want to know their buying preferences for what they purchased, in what color or size.

Perhaps when you query you can add by city or state, giving greater insight when coupling phone numbers. These languages are powerful and do much more than that for sure. Business software systems use some kind of database.

The sky is the limit, and the opportunities are truly endless with large datasets. Businesses have an opportunity to tap into new insights—but first we must all better understand how and why we are doing this.