Structured Data

What is structured data?

Structured data is usually located in relational databases (RDBMS). In them, fields store length-related data-telephone numbers, social security numbers, or postal codes. Even variable-length texts such as names are contained in records, making searching easy. Here, data can be generated by humans or machines, as long as the data is created within an RDBMS structure. This format is eminently searchable using both human-generated queries and algorithms with data type and field names, such as alphabetic or numeric, currency or date.

Common relational database applications using structured data include airline reservation systems, inventory control, sales transactions, and ATM activities. Structured Query Language (SQL) enables querying this type of structured data in relational databases.

Some relational databases store or reference unstructured data, such as customer relationship management (CRM) applications. Integration can be cumbersome at best because memo fields do not conform to traditional database queries. Yet most CRM data is structured.

What is unstructured data?

Unstructured data is essentially everything else. Unstructured data has an internal structure, but is not structured via predefined data models or schemas. It can be textual or non-textual and generated by humans or machines. It can also be stored in a non-relational database such as NoSQL.

Structured vs. unstructured data: What is the difference?

Besides the obvious difference between storing in a relational database and storing outside a database, the biggest difference is the ease of analyzing structured data versus unstructured data. Mature analytics tools exist for structured data, but analytics tools for mining unstructured data are emerging and evolving.

Users can perform simple content searches over textual unstructured data. However, the lack of ordered internal structure defeats the purpose of traditional data mining tools, and the business gets little value from potentially valuable data sources such as Rich Media, network or weblogs, customer interactions, and social media data. Even though unstructured data analytics tools are on the market, no single vendor or toolset is a clear winner. And many customers are reluctant to invest in analytics tools with uncertain development roadmaps.

In addition, there is simply much more unstructured data than structured. Unstructured data accounts for 80% or more of enterprise data and is growing at a rate of 55% or 65% per year.

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FAQ

What is structured data?

Structured data is data that is in an organized format, such as in a database or spreadsheet. They are usually represented as tables, where each column contains a field and each row contains a record.

What is unstructured data?

Unstructured data is data that cannot be inserted into an organized format. They are often stored in the form of text or images that cannot be represented in tables.

Why is structured data better than unstructured data?

Structured data is better than unstructured data because it is easier to process, analyze and visualize. They enable people to understand data faster and use it better.

What are some of the benefits of structured data?

Some of the advantages of structured data are that they are easy to process, analyze and visualize. They also allow for more precise data analysis and preparation.

What are some of the disadvantages of structured data?

Some of the disadvantages of structured data are that it can be difficult to insert and update. It can also be difficult to clean up and structure them if they are not properly maintained.

Why is unstructured data important?

Unstructured data is important because in some cases it can be useful for making decisions or gaining new insights. For example, they can include text on social media that can help understand trends and behaviors.

What are some of the benefits of unstructured data?

Some of the benefits of unstructured data are that it is easy to collect and it can potentially provide new insights and understanding of certain topics.

What are some of the disadvantages of unstructured data?

Some of the disadvantages of unstructured data are that it is more difficult to process, understand and analyze than structured data. Since they are not in an organized format, they usually need to be converted and categorized before they can be processed.

How are structured and unstructured data used?

Structured data is typically used to identify specific trends and patterns in large data sets, while unstructured data is used to gain insight into events and behaviors that are difficult to quantify.

Do structured and unstructured data have their own benefits?

Yes, both types of data have their own advantages. Structured data can be used to identify specific trends and patterns in large data sets, while unstructured data provides insights into events and behaviors that are difficult to quantify.

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Niels Stuck

Niels Stuck has 10 years of SEO experience and is the founder of the SEO agency "WOLF OF SEO". He gained practical experience by building 20+ affiliate sites alongside his marketing studies. Finally, he wrote his bachelor thesis about the influence of SEO on Google rankings, traffic and sales development in the form of a case study. Today, he specializes in e-commerce SEO and helps more than 80 companies build a sustainable organic revenue channel through SEO. Niels advises startups, established brands and corporations in search engine optimization of their online stores and primarily focuses on data-based content strategies and link building. He shares his knowledge about SEO and online marketing in this blog, as a speaker at conferences, in podcasts and as a guest author for OMT, Forbes, Starting Up and many more platforms.

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