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Table of contents
1.
Introduction
2.
Characteristics of unstructured data
3.
Problems faced in storing unstructured data
4.
Solution for storing Unstructured data
5.
Pros Of Unstructured Data
5.1.
Limitless Use
5.2.
Greater Insights
5.3.
Cheaper Storage
6.
Cons Of Unstructured Data
6.1.
Hard To Analyze
6.2.
Data Analytics Tools
6.3.
Numerous Formats
6.4.
Sources of unstructured data
7.
Frequently Asked Questions
7.1.
How is structured data different from unstructured data?
7.2.
Extensible Markup Language(XML) is structured or unstructured data?
7.3.
What are a few ways of extracting information from unstructured data?
7.4.
What is the purpose of unstructured data?
8.
Conclusion
Last Updated: Mar 27, 2024
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Unstructured Data

Author SAURABH ANAND
1 upvote
Master Python: Predicting weather forecasts
Speaker
Ashwin Goyal
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Introduction

Unstructured data is the data that does not correspond to a data model and has no immediately recognized structure, making it difficult to use by a computer program. Because unstructured data is not organized in a pre-defined manner or lacks a pre-defined data model, unstructured data is not suitable for the traditional relational database.

The vast majority of new data generated today is unstructured, driving the development of new platforms and tools for managing and analyzing it. These tools make it easier for companies to use unstructured data for Business Intelligence(BI) and analytics applications.

Although unstructured data has an underlying structure, it lacks a predetermined data model or schema. It might be either textual or nontextual. Either humans or machines can generate it.

Text is the most popular type of unstructured data. Unstructured text is generated and collected in various formats, including Word documents, email messages, PowerPoint presentations, survey replies, contact center transcripts, and blog and social media posts.

Characteristics of unstructured data

In this section, we will learn about the features of unstructured data.

  • Unstructured data is information that lacks a pre-defined data model or is not organized in a particular way.
  • Unstructured data cannot be stored as rows and columns in a database.
  • Unstructured data does not adhere to any rules or semantics.
  • There is no specific format or sequence for unstructured data.
  • The structure of unstructured data is not easily identifiable.
  • Computer programs cannot easily exploit it due to its lack of identifiable form.
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Problems faced in storing unstructured data

Due to unspecific structure, there are various problems faced by unstructured data.

  • Operations such as update, delete, and search is highly complex due to the unclear structure.
  • Unstructured data requires a lot of storage space. As a result, storing videos, photos, audio, and other media is tough.
  • Unstructured data has a higher storage cost than structured data.
  • Indexing the unstructured data is difficult.

Solution for storing Unstructured data

There are a few solutions to the problem of storing unstructured data discussed below.

  • Unstructured data can be stored using a Content Addressable Storage System (CAS). It holds data based on metadata, and each object saved in it is given a unique name. The object is found based on its content rather than its location.
  • Unstructured data can be stored in Extensible Markup Language(XML) format.
  • Unstructured data can be stored in a relational database management system(RDBMS), supporting Binary Large Objects(BLOBs).
  • Unstructured data can be converted to easily readable formats by computer systems.

Pros Of Unstructured Data

Let's see some of the advantages of unstructured data.

Limitless Use

Because unstructured data has no specified purpose, it is highly adaptable. Unstructured data can be utilized in a variety of formats. Unstructured data can be generated through social media posts, video, audio, and free-form text, while structured data is imprisoned in Excel spreadsheets with rows and columns. As a result, unstructured data is more helpful in building use cases and applications than organized data.

Greater Insights

Unstructured data has unmatched power in offering transformative insights. There is more data to work with because an enterprise has more unstructured data than structured data. While unstructured data is harder to evaluate, it may give any company a significant competitive advantage once processed.

Cheaper Storage

Data lakes store structured data, which can be expensive and time-consuming. On the other hand, unstructured data is housed in data warehouses, making it inexpensive to store and quickly access.

Cons Of Unstructured Data

Now we will see some of the disadvantages of unstructured data.

Hard To Analyze

Businesses have been using structured data for years, getting more user-friendly. It can be accessed and analyzed by a typical user familiar with data. Unstructured data is difficult to manage. It will take trained data scientists and analysts to extract value from it in its raw form.

Data Analytics Tools

Excel can be used to extract insights from structured data. But, traditional business tools cannot manage unstructured data. A company that wants to get value from unstructured data should invest in the correct data analytics tool. Not every data analytics tool is made equal. Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies are used in some programs to aid data processing.

Numerous Formats

Unstructured data is available in a variety of formats. Unstructured data can be difficult to evaluate and use when studying a variety of formats such as medical records, social media posts, and emails.

Sources of unstructured data

Unstructured data is available in a variety of formats. Unstructured data can be challenging to evaluate and use when studying a variety of formats such as medical records, social media posts, and emails.

The following list shows a few examples of human-generated unstructured data:

  • Text internal to your company: Consider the amount of text contained in documents, logs, survey results, and emails. Enterprise information makes up a significant portion of the world's text information nowadays.
  • Social media data: This data comes from Facebook, Youtube, LinkedIn, and Flickr, among other social media sites.
  • Mobile data: This contains information such as Short Message Service(SMS) messages and Global Positioning System(GPS) coordinates.
  • Website content: Any site that delivers unstructured content, such as YouTube, Flickr, or Instagram, can cause this.

    Here are some examples of machine-generated unstructured data:
  • Satellite images: This includes weather Data and Information gathered by the government through satellite surveillance photography. Consider Google Earth to get a sense of what I'm talking about (pun intended).
  • Scientific data: Seismic images, atmospheric data, and high-energy physics are all part of this.
  • Photographs and video: This covers video surveillance, security, and traffic surveillance.
  • Radar or sonar data: This covers seismic profiles from vehicles, meteorology, and oceanography.

Frequently Asked Questions

How is structured data different from unstructured data?

Unstructured data is a collection of many different forms of data stored in their native formats, whereas structured data is very particular and stored in a preset format.
 

Extensible Markup Language(XML) is structured or unstructured data?

Extensible Markup Language(XML) is considered to be semi-structured data.
 

What are a few ways of extracting information from unstructured data?

XOLAP (extended online analytic processing) is one of the ways to extract unstructured data. In addition, Taxonomy or classification of data helps organize data in a hierarchical structure. This will make the search process easy.
 

What is the purpose of unstructured data?

Because unstructured data makes up the majority of today's data, businesses must figure out how to handle and analyze it to act on it and make vital business choices. This enables companies to thrive in highly competitive circumstances.

Conclusion

In this article, we have extensively discussed the concepts of unstructured data. We started with introducing unstructured data, characteristics of unstructured data, problems faced while storing them, and finally concluded with the pros and cons of unstructured data.

We hope that this blog has helped you enhance your knowledge regarding unstructured data and if you would like to learn more, check out our articles on data distribution. Do upvote our blog to help other ninjas grow. Happy Coding!

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