Structured data: definition and purpose

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Structured data: definition and purpose
Structured data: definition and purpose

Structured data refers to any type of information that resides in a fixed field in a record or file. They include materials contained in relational databases and spreadsheets.

Characteristics of structured data types

characteristics of structured data
characteristics of structured data

Such material primarily depends on the creation of various business models that will be recorded. And it is also important how they will be stored, processed and used. This includes defining what fields will be stored and how they will store them: a set of structured data, type (numeric, currency, alphabetic, name, date, address, and so on), and any restrictions on entering information. For example, the number of characters is localized by certain conditions, such as lord or lady, male or female, child or adult.

Structured content has the advantage of being easy to enter, store, query, and analyze. At one time, due to the high cost and performance limitations of storing memory and processing relational databases and spreadsheets,the structured materials used were the only way to effectively manage. Anything that didn't fit into the tightly organized structure had to be stored on paper in a closet.

Data management

Working with structured resources is often done using a query language (SQL). It is a common programming language designed to manage and invoke structured data validation in relational database systems.

Structured materials were a huge improvement over strictly paper-based, unstructured systems, but life doesn't always fit into neat little boxes. As a result of all, the first type of data has always had to be supplemented by paper or microfilm storage. As technology performance continued to improve and prices declined, it became possible to introduce unstructured and semi-structured materials into computing systems.

Different kinds

characteristics of different data types
characteristics of different data types

Unstructured data is all those things that can't be easily classified and placed in a neat box or library. Examples include photos and graphics, videos, tool streams, web pages, PDFs, PowerPoint presentations, emails, blog posts, wikis, and word processing documents.

Semi-structured materials are somewhere in between. This view represents a type of structured data analysis, but lacks a rigorous model structure.information. In the case of semi-structured variants, tags or other types of markers are used to identify certain elements, but the information is not rigidly structured.

How to structure data, example: word processing software can now include metadata showing the author's name and creation date, with the bulk of the document being plain text.

Emails have sender, recipient, date, time and other fixed fields added to the content of the email message and any attachments. Photos or other graphics can be tagged with keywords such as creator, date, location, and more to help organize and arrange the graphics. XML and other markup languages are often used to manage semi-structured data.

Technology standards

SQL, a query language, has been a national institute model since 1986. It is determined by the Technical Committee of the Interstate Office for Information Technology Standards. It is worth noting that structured data includes materials and their exchange. The committee has two working groups, one for databases and one for metadata. Participating are HP, CA, IBM, Microsoft, Oracle, Sybase (SAP), and Teradata, as well as several federal government agencies. Both committee draft documents have links to additional information on each. SQL became an International Organization standard in 1987.

And also structured data helps, for example,Google better understand content. This is an important signal if a business wants the site to be visible in search functions.

But should all brands use structured data? Is it worth it? The short answer is yes, of course.

But before we get to the full answer, we need to clear up a misconception: structuring data is just building an SEO strategy. This needs to be understood.

Structured data is the basis for machines to make sense of all content.

It's like a relationship between a customer and a supplier: the more information you have about a buyer's SEO problems, the better you can solve them. To do this, you need to know what problems they had previously. This is the main secret of creating a strategy for success.

Brands hope that machines like Google, Alexa and Siri will read and understand content effectively and efficiently.

Using schema markup, however, gives them control over how their information is defined, in turn to control the machine's understanding of the whole structure.

Reusable structured data

data types
data types

This type of information has been around for many decades.

It was more limited a while ago, but now you can find it here for just about anything, including recipes, jobs and restaurants, and more.

In fact, Richard Wallis, a consultant working on Schema project support at Google, summarizes that this type of materialfeatured in every published post on any brand's website.

Key takeaway: Use of structured data is on the rise and currently accounts for about a third of all websites crawled.

This is because the big brands tested the resources with their time and they were able to correlate the results with business values such as improving traffic or generating conversions.

Structuring data not only provides great search benefits, such as reusing information to improve analytics or location, it also provides voice benefits, such as informing chatbots.

By structuring information, owners help define content to improve the chances of machines correctly matching content to relevant voice queries. In fact, for example, Amazon says it uses a schema to determine the intent of a local business.


structured data types
structured data types

A hospitality client was recently tested to see the full impact of structured data.

First of all, a local scheme of lists and breadcrumbs was implemented on the main page.

As a result, mobile CTR improved slightly from 2.7 percent in Q1 to 2.8 in Q2.

So far this was a short test, but it is expected that in the next nine months the number of clicks on this project will increase by 5-10%.

Besides,this experience led to some more results:

  • Clicks increased by 43 percent.
  • Impressions up almost 1.
  • The average position also increased by 12 percent.

The meaning of structured data used to be just to get rich results from Google or Yandex. Now the value extends further to the quality of the movement measures.

Search Pages has published several case studies that provide examples of how the scheme is used for some major brands.

Top 5 Reasons Many Companies Don't Use Templates

Watching many pages, you will notice that some holders, for a number of reasons, do not have structured data. Here are the main problems:

  • They have no resources.
  • They are not technicians (and they don't have the right specialist) and don't understand code and how to label items.
  • The site is not supported by their CMS.
  • They don't see or understand the benefits.
  • Behind the times and stuck in the past.

Fortunately, there are some great solutions on the market that allow you to scale and easily create, manage, and measure structured data.

Main Benefits of Using Schema

data characteristics
data characteristics

There are many positive aspects of this product, especially for e-commerce brands. Here are some top benefits.

Higher CTR

characteristics of data types
characteristics of data types

AvailabilityRich snippets for products in search results are a great way to improve click through rates and get more attention for your ads. This is especially evident if there are excellent product reviews.

More conversions

Having rich snippets can also increase the ratio, because if a lot of people see the ads and they are positive, the likelihood that people will buy on the required platform will increase.

For job sites, ever since Google launched Jobs and companies like ZipRecruiter implemented structured job data, their articles get more exposure and conversions by showing related queries.

Getting featured snippets is the "Holy Grail" for SEO. The site will appear at the top of the search results page, in front of organic listings. Structured data isn't necessary, but it can sometimes help you get a featured snippet. This can increase click through rates and drive more traffic.


Unfortunately, some things are often abused by SEO sites.

Don't become a spammer when using structured data. Only materials that are relevant to the content should be used.

If the owner does not follow this rule, you can get a manual action from Google or "Yandex" with spam structured data, as a result of which the entire site or individual articles will not be displayed in search results. Last it untiluntil all information is cleared.

And also make sure that all structured data has been updated. Everything is constantly changing, and therefore new trends are constantly emerging, including in the dissemination of information.


characteristics of structured types
characteristics of structured types

Don't ignore structured data. Organic search is getting more and more competitive. Any additional information you can provide to search engines helps:

  • Increase CTR.
  • Improve search engine visibility.
  • By displaying selected snippets in the knowledge graph, we can help machines solve user problems.

More structured data resources:

Google and Yandex confirm that this type of information improves targeting.

And they also specify how much structured data is enough for certain models.

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