Every day, companies create more data than ever before. But what is unstructured data? And can it help your business?
Unstructured data is the huge amount of information that a company’s employees, customers, and products generate through research. It includes audio recordings, video recordings, images, documents in different formats, and even social media posts. The research shows that data warehouses are becoming bloated with unstructured information at a rate that outpaces the capacity of current, largely manual processing techniques.
While this may sound like a lot of information—and it certainly is—it’s also incredibly valuable. It provides insight into how people think about your products and services and how they interact with them. It allows you to see what’s working well and why it’s working well so that you can improve upon it and create more effective strategies in the future.
Read on to find out how this blog post can help you understand unstructured data and how you can use it to improve your business.
Structured Data Vs. Unstructured Data Vs. Semi-Structured Data
Structured, unstructured, and semi-structured data are the most common categories that describe data in practice. These types of data are defined by their storage and their ease of access and analysis.
Computers can easily identify and understand structured data because it has a specific format and structure. Structured data is more common than unstructured data because it’s easier to collect, analyze and store. Structured data is organized into columns and rows in a database or spreadsheet. You can search for it using keywords or other search parameters. A relational database management system (RDBMS) stores and makes available structured data in the form of interconnected rows and columns. A common type of structured data is stored in a database or database table in a predetermined way, such as by phone number or address.
Itinerary planning software, stock-taking databases, and financial payments all fall under structured data systems.
Unstructured data doesn’t have any predefined structure or format. It could include word documents, emails, audio files, or video files — basically any digital content that isn’t structured.
This type of data is unorganized and unpredictable. It’s a broad category that includes many data types, such as images, audio files, text documents, and videos.
It can be found in various locations and forms. For example, emails are unstructured because they aren’t in a predefined format. This makes it difficult for companies to store, manage and analyze the information contained in these messages.
Learn more about these types of data here!
Semi-structured data is a subset of unstructured data organized into categories or fields but still lacks a rigid structure. While semi-structured data is still mainly unstructured, it uses tags and markers to internally identify and match distinct data items into hierarchies and relationships.
As an example, consider email. Email analytics solutions can categorize messages and perform keyword searches using metadata. XML and NoSQL databases, as well as the data collected from sensors and social media platforms, are examples of semi-structured data being improved for searchability.
What Types Of Unstructured Data Exist?
You can find it in many different places like:
- Documents such as emails, Word documents, PDFs, etc.
- Emails, social media posts, and comments are analyzed using natural language processing (NLP) methods.
- Audio recordings such as phone calls or radio broadcasts.
- Customer feedback from online reviews, surveys, and unsought social media posts.
- Visuals include images, photos, screenshots, videos, and other visual media files.
- Video files such as security camera footage.
- The form of audio files is saved anywhere in databases.
How Can You Utilize Unstructured Data?
There are many ways to utilize unstructured data to gain insights into your customers. One of the most popular methods is machine learning algorithms that can analyze content and extract insights from it. One can do this through keyword searches or natural language processing (NLP).
Text mining is another process that allows you to analyze unstructured text data and find patterns within it. You can use text mining to find similar topics across different documents or find trends within your product reviews.
Here’s how you can use it to:
- analyze messages to ensure they are in line with rules and regulations
- monitor and assess social media activity involving clients
- gain a solid understanding of typical consumer habits and inclinations
Why Do We Need To Analyze Unstructured Data?
Businesses often use unstructured data to learn more about their customers for marketing purposes. This information is also useful for research purposes and for documenting events and activities within organizations.
Unstructured data can be difficult to manage because it does not follow specific rules or regulations regarding storage or retrieval processes. To properly store this type of data, organizations must utilize the right tools and software programs that will help them keep track of where each piece of information resides within an organization’s network system.
There are many reasons why analyzing this type of data is important for businesses:
- It can help find new business opportunities, such as new customers or leads, by showing us what people say about our brand or products on social media sites like Twitter or Facebook.
- Helps find information about competitors’ products and services. Hence, we know what features they offer and how much they cost so we can make better decisions about what we should offer customers ourselves.
- It can help us identify new trends in our industry, so we know whether or not our products are meeting consumer demand.
- It can help businesses uncover new opportunities by helping them understand their customers better. This can lead to innovation and product development which will help you stand out from your competitors.
Take A Way: Unstructured Data Is Worth Finding Ways To Harness
A huge field of study, unstructured data is growing rapidly and will only get bigger. It’s not just about making the most of what you already have—it’s about able to organize and understand the massive amounts of data that are constantly coming in. If you want to be able to make sense of this kind of information, you need to know how to use analysis tools like Speak Ai.
Speak Ai is designed with the user experience in mind. It helps you quickly make sense of large amounts of unstructured data, so it doesn’t matter if you’re working with hundreds or thousands of documents or files—Speak Ai will help you find what matters quickly and easily.
This tool offers cutting-edge resources to businesses for extracting value from unstructured data. Therefore, join the 7,000+ teams already using Speak Ai to record and analyze their unstructured language data. If you want to streamline your processes, find new sources of income, and keep doing what you love, sign up for a trial or schedule a demonstration now.