HomeContributionsHow Does Unstructured, Semi-Structured, and Structured Data Differ?

How Does Unstructured, Semi-Structured, and Structured Data Differ?


This article was contributed by James Allison who works as editor for for Globex Outreach.

Data analysts will routinely have to work with new information that their company collects. But, as we know, not all data is created or received equally. While some data will be neat, ordered, and easy to analyze with SQL, other pieces of data will escape categorization.

Data comes in three primary forms, known as structured, unstructured, and semi-structured data. Depending on its ability to be categorized, it will align with the characteristics of one of these three formats. As we progress further into our digital age, most data is unstructured. However, it's essential to understand all three types to extract high-impact analysis for a business.

Typically, we'll see businesses using various tools and strategies to manage their data, not favoring one type over any other.

In this article, we'll dive into each of these structures' main characteristics and advantages, demonstrating why it's important to understand them when using a Windows system. Let's jump right into it.

What Is Structured Data?

Structured data is any data that is lined into neat categories. Instead of having a range of different units or file types, structured data is always formatted and extremely easy to order. You'll often find structured data in a database, as using SQL to query tables with columns and rows is typical.

The critical factor that defines structured data is its ability to be placed into pre-designed fields. Instead of creating new categories for unique data points, structured data will all fit into your expected format or structure. Due to this, it is highly regular and is one of the easiest ways of managing information.

Structured data comes with a range of advantages, making it the go-to format for many data engineers:

  • Easy Integration – Structured data can integrate with various platforms and tools. As this data structure has been used for considerably longer within businesses, data analysts have already developed various tools and systems that help users interact with the structured data they produce. You have a much greater tool selection and flexibility when interacting with this data type.
  • Human-Readable – We are surrounded by structured data every single day. With its commonality and clear structure, you'd be hard-pressed to find someone that doesn't understand how to read and interpret structured data.
  • AI-Compatible – AI and ML tools can rapidly digest structured data and assimilate it into their understanding. Due to its order, you can train tools to interact with structured data and quickly produce insights for your business.

What is Unstructured Data?

Unstructured data is the direct opposite of the aforementioned structured data. While the former was about order and traceable relationships, unstructured data is difficult to organize and comes in many different forms.

While unstructured data may seem like a strange choice for organizations, businesses continually use it in their operations. This is because the vast majority of information collected online comes as unstructured data. The world is not logical enough to deliver highly-customized and neat tables for every interaction.

Instead, we get PDFs, word files, media logs, and snippets from conversations across . Unstructured data is everywhere, accounting for around 80-90% of all data collected online. Although not ideal, unstructured data isn't quite as challenging to manage as many people make out.

Although it can be intimidating to people that don't know what they're doing, unstructured data does hold a unique set of benefits for data engineers:

  • Further Insight – Sometimes, the very best business insights are not on a superficial level. If you want to learn more about your customer base, their traits, consumer habits, or psychographics, there is very little chance of doing so with structured data. Unstructured data, in its many forms, can be used to gain much greater insights for your business, helping you drive for success in the long run.
  • Collection Speed – Businesses can harvest unstructured data at incredible rates without needing to format or carefully section information. As most data online is unstructured, businesses can easily collect large quantities for analysis — the more data, the merrier – with more extensive databases helping companies conduct more specific research.
  • Flexibility – Structured data will only come in a few select formats. Unstructured data, on the other hand, can be nearly anything. This additional flexibility can lead to better research and development.

What is Semi-Structured Data?

Finally, we come to semi-structured data, which lies between the two previous data structures. Semi-structured data doesn't exist within a relational database as structured data does. Yet, parts of it will have organizational properties, meaning it can be paired with predefined data models, unlike unstructured data.

Sitting in the middle, semi-structured data is all about half measures. At the same time, some of the information in a data set will fit into regular categories. This balance allows data engineers to store some data within relational databases.

If you're using a Windows system, you'll likely already have an indexer who understands semi-structured data to a greater extent. However, if you're using an alternative approach, you might need to configure your platform to work with this data type.

Most semi-structured data will use Resource Description Framework (RDF) or XML technology. At the awkward in-between stage between structured and unstructured, this form of data doesn't have nearly the same range of benefits as the others will offer you. That said, there are some advantages of semi-structured data:

  • Tool Choice – As you can work with structured or unstructured data tools, you have a greater selection of what you'd like to use.
  • Analysis Style – With semi-structured data, you can use SQL or an unstructured language to interact with the data, depending on your final intent.

Final Thoughts

Unstructured, structured, and semi-structured data have their place in our world of data. As the online space, we work in becomes increasingly complicated, we're likely to see a further increase in the amount of unstructured and semi-structured data we produce.

However, structured data also has a range of uses. If you're working on a Windows system, it's essential to understand how to use and interact with each of these data types. With true mastery of each, you can poll, query, and interact with data to gain world-class business analytics.

About the author

James Allison oversees content writing services at Globex Outreach. He uses his five years of experience to write content that always meets clients' expectations and goals.

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