Structured vs Unstructured Data: The Ultimate Guide

Every bit of data your company owns has the potential to give you a competitive edge in the marketplace. But only if you know how to connect the dots and extract real insights from that data.

Becoming a data-driven organization requires tapping into the power of big data. To do that, you need to know the most effective tools to use for both structured and unstructured data. And most important, you need to know why both data types are crucial to the future of your company.

What is structured data?

Structured data is made up of numbers or text that can fit into predefined fields. This data classification typically resides in the rows and columns of a database. While it is the easiest kind of data to search and analyze, it represents only about 20% of all data.

Structured data examples include: location data from smart phones, star ratings by customers, demographic information, customer addresses, or purchase history.

What is unstructured data?

Unstructured data is any information that doesn’t fit neatly into a database. Because it lacks any real structure, this data classification is much more difficult to collect, process, search and analyze.

Unstructured data can contain a wealth of hidden value. But companies often discard it, because extracting meaningful information is problematic.

Unstructured data examples include scientific publications, parts manuals, financial prospectuses, any other data that doesn’t fit into rows and columns.

What is semi-structured data?

Semi-structured data is essentially a mixture of structured and unstructured data. It may have some structural elements, such as names, time stamps, or device IDs. But it doesn’t have a rigid structural framework. That makes it difficult or impossible to fit semi-structured data into a database.

Some data that at first appears to be unstructured may in fact be semi-structured. If it contains some classifying characteristics, it’s likely semi-structured data.

Semi-structured data examples include HTML code, CSV documents, email messages, or any data that can be organized in some way but isn’t easily extracted into a database.

What’s the difference between structured and unstructured data?

Analyzing structured data is especially useful for showing important relationships. For example, ‘existing customers’ who have ‘purchased product X’ but have not ‘purchased product Y’.

Extracting information from unstructured data is more difficult. Since it can’t be organized into a row-column database, tools such as regression analysis and pivot tables won’t work. As a result, organizations often make the mistake of ignoring their unstructured data.

Why Is Data Strategically Important to Your Company?

Being able to access and search both structured and unstructured data is game-changing. It opens up possibilities for your company that may have never existed before. You gain clarity about your customers, your competition, and your own company. As a result, you can make informed decisions that give you a strategic advantage in the marketplace.

Data helps you better understand performance.

Most companies go about setting performance targets the wrong way. They look back at actual past performance or make comparisons to industry benchmarks.

The problem with that approach is that it’s only an educated guess. It can lead to assigning performance targets that are either too aggressive to be achievable, or too conservative to move the needle.

The best way to figure out your theoretical best performance targets is to look at your data. Both data types can help you calculate more accurate performance targets.

That helps your organization drive potential revenue, reduce costs, and find operational efficiencies.

Data helps you make better business decisions.

Big data empowers you to make better data-driven decisions. The power of your data frees you from relying on opinions or industry standard practices.

Your data can help you figure out which marketing initiatives have the greatest potential, for example. Or it can show you which of your offerings would be most appealing to your target market. That can help you make better decisions about product development.

In every area of your business, your data can tell you which activities should offer the greatest ROI.

Data helps you better understand consumers.

Structured data tells you the things that you already know about your customers. Who they are, what they buy, and so on.

Unstructured data helps your understand what you wouldn’t otherwise know about. Consolidating information from various sources, such as social media mentions or online reviews, can tell you a great deal.

Finding these hidden patterns can reveal which of your products and services are the most delightful to your target audience.

Big data can also help you identify patterns in customer behavior. That gives you the information you need to make the right decisions to improve customer relationships.

How to Exploit Structured and Unstructured Data

Unstructured data accounts for almost 80% of big data. If you aren’t gaining business intelligence from your unstructured data, you’re missing most of the big picture.

Find the right tools for structured vs unstructured data.

For years, companies have mined their troves of structured data to find useful information. But there’s a limit to how much your structured data can tell you.

Extracting actionable insights from unstructured data has always presented a challenge. But that’s already changing.

The latest generation of big data tools are powered by artificial intelligence algorithms. They can process massive amounts of raw unstructured data with greater accuracy than ever before.

These tools make it possible for organizations to unlock the value in their vast troves of unstructured data.

The key to unstructured data is cognitive search.

Cognitive search taps into the power of artificial intelligence to dig deep into unstructured data. It understands not only the information you’re looking for, but also the intent behind that request.

It recognizes the patterns and relationships within the data as a whole, and extracts contextual insights. This gives you the unprecedented ability to understand your data better than ever before.

Over time, as more data becomes available, cognitive search continuously learns and adapts. That means it provides you with more than just information. It also gives you a strategic advantage.