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Types of Data: Unstructured vs Structured Data – What’s The Difference?

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Unstructured Vs Structured Data

Big data is a term that catches attention of everyone today.

This attention can be justified through some surveys and facts. These surveys and facts says that each and every second we all users are creating a new data which gives addition to the rate of data growth.

Unstructured vs Structured Data - DifferencesMost of the web applications like facebook, twitter, instagram, and youtube are the ones which connects with 1 billion people every day, and these people not only survey but share and create new data every single second.

Survey says that the amount of digital universe will double in every two years.

Many organizations are working on data driven projects, most of them don’t consider web data as dead data where as different research centers using this data for analysis purpose are trying to utilize it for business intelligence and pattern prediction.

How many types of data do we have?.

There are about 13 different types, but in this post, I’ll be focusing on structured data and unstructured data, then we outline the differences between them.

Unstructured vs Structured Data - Data Types

Unstructured Data

It includes videos, images, and audios.

Today, in our digital universe 90% of data which is increasing is unstructured data. This data is not fit for relational database and in order to make them store, scenario came up with NoSQL database.

Today there are four families of NoSQL database, they include:

  • Key-value
  • Column-oriented
  • Graph-oriented
  • Document-oriented

Most of the famous organizations today (amazon, linkedln, facebook, google, youtube) are dealing with NoSQL data.

Structured Data

Structured data concerns all data which can be stored in database SQL in table with rows and columns. They have relational key and can be easily mapped into pre-designed fields.

It is highly organized information that uploads neatly into a relational database

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Structured data is relatively simple to enter, store, query, and analyze, but it must be strictly defined in terms of field name and type.

Data in CSV files, XML files, JSON files, email headers, and to some extent HTML is structured, because once you have the format specifier for a particular file, you can easily identify specific values in the data and what they mean semantically.

A whole lot of business-gathered data is in lists, tables, or other structured formats.

Unstructured Vs Structured Data: Differences

Now let’s come to the differences.

Structured Data:

  • Can be displayed in rows and columns or in other words an excel spreadsheet.
  • Could be number, date or a string usually a text value.
  • It also requires less storage area as compared to unstructured data.
  • It can be managed and protected easily.

Unstructured Data:

  • It cannot be displayed in rows and columns.
  • It includes images, videos, emails, audios.
  • It can’t be stored in traditional database systems.
  • It is hard for nontechnical business users and data analysts alike to unbox, understand, and prepare for analytic use.
  • It is difficult to define unstructured data in a defined data model.

Moreover, both data types can be stored in either relational and non-relational databases, and the choice of database technology for analyzing data is more complex.

Conclusion

Gowing data directly influence its related data models and database technologies, it represents that, big data concept not only deals with huge and vast data but it gives a new gate to database analyst and researchers to work on various data and data models for survival of new kinds of data in upcoming and present scenario.

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