When Data Grows Too Large: The Need for Structured Data

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When Data Grows Too Large: The Need for Structured Data

  • 06/02/2023

When Data Grows Too Large: The Need for Structured Data

  • 06/02/2023

When Data Grows Too Large: The Need for Structured Data

  • 06/02/2023

When Data Grows Too Large: The Need for Structured Data

  • 06/02/2023

When Data Grows Too Large: The Need for Structured Data

  • 06/02/2023

Big data definition and the significance of structured data

Data scientists frequently use the three Vs of big data: volume, velocity, and variety.

Volume

Every day, data is produced in excess of 2.5 quintillion bytes worldwide. By 2025, it is anticipated that 5.2 zettabytes of data will be available for analysis.

Velocity

People are producing data at an unprecedented rate. 90% of the data in existence in 2018 had been produced between 2016 and 2017. By compiling actual web click events, the 2020s are already being established. The only time data velocity will decrease when humans cease producing it. That’s probably not going to happen until there’s a zombie apocalypse.

Variety

Data can also be found in unstructured forms (strictly formatted files like spreadsheets). 80% of the data in the world is thought to be unstructured (social media activity, .wav files, videos, graph collections, emails, text messages, and chats).

With the amount of unstructured data that is being produced at such a rapid rate, it is obvious that how we use the data, not its bulk is what is important. We need structured data to fully utilize all of this information’s potential and make it readable by machines. We’ll find out how quickly and effectively you can process and use data at scale. But first, it’s important to clarify the distinctions between structured and unstructured data.

What are structured data sets?

When we talk about structured data, we imply information that has been categorized using a rigorous schema and a specified data model. A data schema describes how data is organized and serves as a blueprint for building a database.

There are components of structured data that can be employed in the real-world analysis. Structured data is any information in a database as a table with rows and columns.

Do any concrete examples of structured data come to mind? Imagine an HR department with a database of employees. This database would contain specific employee data, such as birthdate, hire date, salary, etc. Structured data includes pretty much anything that can be entered into an Excel spreadsheet.

What are unstructured data?

It’s a little misleading to call data unstructured. It does have an internal structure, but when we collected it, we lacked a data model or schema. After collection, we might clean it up and organize it.

Emails, papers, texts, videos, and other types of unstructured data are included. Metadata (such as the date sent/modified, author, and sender) may be included with such files. Despite the possibility of structured metadata (more on that later), rows and columns are not used to organize the information.

Discover how Hir Infotech provides organized data.

Your one-stop shop for automation and data extraction is Hir Infotech. Data collected from websites and databases can be automated with the use of web scraping solutions from Hir Infotech. This implies that you can gather structured or semi-structured data fast and effectively without writing any code and then combine that data with external models. When you have the information you need, you may download it in various organized formats, including HTML tables, JSON, CSV, Excel, XML, and RSS feeds.

Frequently asked questions:

What is structured in large-scale data?

Data that is properly arranged and kept in databases, datasets, and spreadsheets is known as structured data. Traditional analytics tools can easily read this data. Although time-consuming, turning unstructured data into structured data is doable with the appropriate solution.

How would you define big data?

Data that is too big, moving too quickly, or complex to process using conventional techniques, is referred to as big data. Long before analytics became popular, people would access and store vast volumes of data.

Which three types of structured data are there?

There are three forms of data: unstructured, semi-structured, and structured.

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At Hir Infotech, we know that every dollar you spend on your business is an investment, and when you don’t get a return on that investment, it’s money down the drain. To ensure that we’re the right business with you before you spend a single dollar, and to make working with us as easy as possible, we offer free quotes for your project.

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Request a free quote

At Hir Infotech, we know that every dollar you spend on your business is an investment, and when you don’t get a return on that investment, it’s money down the drain. To ensure that we’re the right business with you before you spend a single dollar, and to make working with us as easy as possible, we offer free quotes for your project.

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Request a free quote

At Hir Infotech, we know that every dollar you spend on your business is an investment, and when you don’t get a return on that investment, it’s money down the drain. To ensure that we’re the right business with you before you spend a single dollar, and to make working with us as easy as possible, we offer free quotes for your project.

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Request a free quote

At Hir Infotech, we know that every dollar you spend on your business is an investment, and when you don’t get a return on that investment, it’s money down the drain. To ensure that we’re the right business with you before you spend a single dollar, and to make working with us as easy as possible, we offer free quotes for your project.

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