For centuries, historians and analysts have worked tirelessly to decipher special meaning from a number of texts. Just think of how many times the Bible has been translated by different scholars. It makes sense that we analyze these historic works with a lot of care because there wasn’t as much writing or access to information centuries ago. Today, on the other hand, there is almost too much information at our fingertips. The internet is full of data and information that anyone can publish at any time. Just because there’s a lot more data from various different sources doesn’t mean that information is any less valuable.

As a company or organization, you want to mine information and analytics from text the same way those scholars do. The more you can understand this unstructured data and group it into different areas, the better decisions you’ll be able to make for your company as a whole. Text mining and text analytics are terrific techniques that help you find patterns and understand your large amounts of data in new, creative ways. Let’s dive deeper into how these text analysis platforms work and the different use cases for your business.

What is text analysis?

First, it’s important to understand the definition of text analysis. This is a business intelligence platform that uses machine learning, statistical platforms, and linguistics methods to turn unstructured data and text into defined formats that can offer insights and visualized patterns. Different organizations, including businesses, researchers, political groups, and the media, can benefit from these techniques to predict future trends and outcomes for their organizations. There is so much data and text out there for you to gain information from. You just need the right tools to process it effectively. A text analyzer will do just that automatically while offering you a detailed view of your customer responses. By combing through blogs, reviews, forums, news sites, and more, text analysis can help you make smarter business decisions for the future of your organization.

How are text mining and text analysis linked?

A data analyzer will work in a few different ways. To get to the analysis, you need to start with mining. While text mining and text analytics are typically interchangeable terms, there is a slight difference between the two. You start out with text mining as a way of gathering information within your analyzers. This is where you get your insights. Take things to the next level with text analysis. This is where you can actually measure results and see quantitative data.

What steps are involved in text analytics?

There is a natural set of steps to deciphering your text mining. You have to start with gathering information. Bring together details from customer reviews, online forums, social media posts, and news sites to see what people are saying and how it affects your company. From there, you can perform your preparation. This goes down to the basics of text with things like formulation, part-of-speech tagging, and parsing. Breaking down everything to a very basic level helps you move on to text analytics. Actually see insights once you have a foundation for your data to be structured into. Your machine learning can help you extract and classify these new items to make modifications for the best future outcomes.

How does text analytics benefit my organization?

Text analytics is all about turning unstructured data into structured information. Once you have those details, you can see visualizations and make models based on facts. Don’t settle for disorganized workflows. Instead, rely on text analytics to gain new insights and process your information in the most effective way.

Danny Watson