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GuidesResearch methodsWhat is structured data?

What is structured data?

Last updated

27 February 2023


Dovetail Editorial Team

Reviewed by

Hugh Good

According to IBM, structured data is "highly organized and easily decipherable by machine learning algorithms." It’s a type of quantitative data. In 1974, IBM developed Structured Query Language (SQL) for structured data. It also created a SQL database to sort that data to make it easily accessible.

So, what is the difference between structured and unstructured data? In this piece, we’ll look at both, focusing on structured data.

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What do you do with structured data?

Structured data works with programs and algorithms. It can be as simple as the price, size, and material of a shirt you sell online. Google quickly understands these bits of data, so it can include them in search results, creating a richer, more dynamic result for the searcher. 

Why do we need structured data?

Although structured data is a must-have in today’s online world, not all businesses use it. 

Using this form of data ensures search engines include your brand and products when people are looking for your company or product. 

Characteristics of structured data

  • A well-defined structure

  • Has a persistent order

  • Easy-to-access

  • Standardized format

  • Usually stored in a database

  • Data model compliant

Pros and cons of structured data

Structured data has several benefits, including:

  • Its user-friendly style and easy access 

  • Being perfect for machine learning (ML) algorithms

  • Tools can use and analyze it easier than unstructured data

However, it also has drawbacks:

  • Data inflexibility

  • Limited storage options mean you have to completely update it if there’s a change in requirements

Alternatives to structured data

The alternative to structured data is unstructured data. 

Unstructured data is not pre-defined, and you can’t store it within a relational database management system (RDBMS). It is difficult to process and analyze and doesn't have a consistent internal structure. Because of this, unstructured data is difficult or impossible for data mining. 

Most companies still use unstructured data and miss out on the customer interaction and social media convenience of structured data.

Structured data format

Structured data falls into the tabular format with rows and columns. Structured rows and columns make it easily accessible to people or machines. Examples are SQL databases and Excel files.

Structured data guidelines

Guidelines for Google structured data deal with technical and quality guidelines.


  • Format markup must be either JavaScript Object Notation (JSON-LD), Resource Description Framework (RDF), or Microdata

  • Do not block access using noindex, robots.txt, or other access controls


  • Follow anti-spam rules

  • Content should be up-to-date, relevant, and original

  • Do not use fake reviews or other misleading aspects

  • All markup content must be visible

  • Your data must reflect the content on the page

  • You must complete all required properties for the specific rich result type

  • Structured data must be on the page that it is describing

  • Images must be relevant

  • Image URLs must be indexable and crawlable

Structured data tools


This open-source relational database management system (RDBMS) puts data into collections and organizes it.


OLAP is an acronym meaning Online Analytical Processing. It’s a computation method that allows users to get data and query data to analyze in high-speed conditions from centralized storage.


Also known as Postgres, PostgreSQL is an open-source RDBMS that supports languages like Python, Java, JSON, and SQL.


Programmed in the C language, SQLite is a non-standalone software library database engine that is serverless and transactional relational.

Use cases for structured data

Structured data use case examples include:

  • Accounting firms that need to record financial transactions and process the results

  • Travel agencies and service industries that make online bookings with dates, addresses, phone numbers, etc.

Advantages of structured data

One of the main advantages of a structured data arrangement is the boost to indexing from content organization, as it’s simply more efficient. There is also a higher click-through rate to your website listings, giving you higher conversion rates. 

Structured data: 

  • Increases your online visibility

  • More easily moves you in search engine rankings 

  • Allows more people to click on your offerings

  • Gives you a better conversion rate than without it

This means your company can sell more of your product with the content than without it.

Test your structured data

You can use the Google Structured Data Testing Tool to test your structured data. This tool is user-friendly and allows you to put in the code you want to check or paste the URL of the page you want to test. Google will run it and notify you of any issues. You can test RDFa, Microdata formats, and JSON-LD with the Google Structured Data Testing Tool.

Structured data helps man and machine talk. It gives programs and algorithms simple, bite-sized pieces of information. They can process your data quickly, increasing your website's search visibility.


What is structured data (with example)?

Structured data uses data models to determine how you process, access, and store that data.

Typical examples of structured data usage include: 

  • Invoicing software

  • Contact lists

  • Some customer relationship management (CRM) systems

  • SQL databases 

  • Excel files

What is structured vs. unstructured data?

The key difference between structured and unstructured data is that structured is quantitative, and unstructured is qualitative.

Structured data adheres to a format and is easily accessible, while unstructured does not and is not.

The tabular format for structured data makes it easier to store, and it requires less space than unstructured data, which does not follow a format and takes up more space.

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