5 Widely used Tools and Techniques for Text Analytics

 Text analytics solutions that helps in the extraction of structured data of supreme quality from the unstructured text.

It is referred to as text mining. One of the prominent reasons owing to which people use it is for the extraction of additional data from the unstructured data sources with an eye to enriching the master data of the customers with an eye to production the new customer insight.

It is also useful for the determination of sentiments and different types of products and services.

Results of the survey, tweets, online reviews, emails and different kinds of written feedback consist of insight into the customers.

The recorded interactions have a bunch of information that can be transformed into the text without any hassles.

With the aid of text analytics software, you will be capable of uncovering a wide array of themes and patterns.

Thus, you will have an information about the thoughts of your customers. With it, you will be able to gain an understanding of their requirements and needs.

So here we will discuss about the top text analytics tools and techniques which  is avail in the market. And before going through the topic i assured you that this will be more helpful for beginners. Okay lets jump into the topic.

Text analytics solutions with Hadoop:

Analyzing text with the aid of Hadoop happens to be an amazing option when the full volume of the source files is huge and the Hadoop Cluster has prerequisite sources.

Thus, the application of text analytics tool happens more quickly in Hadoop. The text analysis is known for the extraction of entities from the unstructured text.

It is helpful for the transformation of the unstructured data into the structured data. This is crucial for running any sort of analysis with the aid of the data in text resources.

You just require the text sources as the input for text analytics solutions.

Later on, you can remove the text sources theoretically, as they will not be required for the process of analysis.

Text analytics solutions with HANA

With the aid of SAP HANA, it is possible to extract real insight from the unstructured data.

This platform stands out of the ordinary in offering text analysis, search and text mining functionality from the unstructured text sources.

Statistical algorithms can be applied by which you can detect the patterns in the large document collections, which is inclusive of key term identification as well as document.

Almost 80 percent of the relevant information of the enterprise is derived from the unstructured data.

With the aid of SAP HANA, you can get access to the greater volume of data that is inclusive of unstructured text data from a wide array of sources. SAP HANA allows people to do the full-text analysis.

Text analytics solutions with R

Here is the list of the leading four options that are used in the big data industry with an eye to accomplishing text analysis process in R:

• Keyword Match Algorithm
• Word match algorithm
• General Expressions

It has a tendency for capturing the trends that do not indicate anything significant.

Text analytics Solution with Excel

Excel is recognized to be an effective and convenient solution for accomplishing your requirements for text analysis.

You can go for an analysis of several customer reviews for gaining an insight into the product.

The Excel add-in functions on ParallelDots AI APIs that are used by the enterprises and developers for empowering the analytics for the past two years.

You can conduct keyword analysis on a bunch of negative and positive sentences with an eye to understanding why people are disliking or liking the product.

This text analytics solutions let you get an insight into the key phrases that contribute to the sentiment about the product.

Text analytics solution with Python

Here are some of the applications in which python stays at the forefront that enable the use of a wide assortment of advanced libraries, specifically the natural language processing toolkit.

It comprises of a series of libraries and advanced functions for the performance of specific operation present in the text for pre-processing it for using the same for the derivation of information from the same.

Sentimental analysis solution

During online shopping, most of the customers provide feedback. This feedback is classified into the categories like negative, positive and neutral, thereby letting the customers make a better-purchased decision about the product.

It also helps the company in filtering out the flaws from the negative reviews for the improvement of the product.

Conclusion

The text analytics is known for conferring the early warning of the trouble as it showcases the points, your clients are not satisfied with.

With the aid of the text analytics tool, you will gain success in extracting valuable details from the data that cannot be quantified in the other ways at ease.

It is useful in turning the unstructured thoughts of customers into the unstructured data at ease that you can use for your business.

The Content first presented in Indium Software blog

Text Analytics Tools: What and Why? Beginners Guide

In the time of advanced technologies, organizations are grasping the need to comprehend organization information more than ever. Text Analytics Tool/Software has gotten a consistent activity for almost every CIO over the previous decade. A later part of examination and business knowledge is the need to comprehend organized information, yet unstructured information too.

Key Specialities/Benefits with Text Analytics Tool:

• Rapidly comprehend and pull slant examination, key expressions, topics, and different bits of knowledge from unstructured content information 
• Consolidate an assortment of unstructured information sources and picture the information in an effectively understandable way 
• Expel noteworthy bits of knowledge from content that can affect various regions of a business

Reason for using Text Analytics Tool

The motivation to utilize text analytics software is somewhat clear—you have to break down content—however there are numerous explanations for why a business might need to perform content mining and examination.

1. Understand Customer Sentiment
2. Understand Employee Sentiment
3. Easy Feedback Analysis
4. Text Classification
5. Business Improvement for Text Summarization

Where Text Analytics Software/Tool Use:

There are various capacities of text analytics tool that can assist clients with pulling business-basic experiences from content information.

Language Detection: 

Text analytics tool give clients the capacity to comprehend which language the content was written in

Tagging: 

When the language is recognized, text analytics software can label each word with a grammatical feature, implying if the word is a thing, action word, descriptive word, etc. 

Text Parsing: 

Keyword parsing is fundamentally the same as a feature of discourse labeling, yet as opposed to seeing each word, it assists break with bringing down how a sentence was built and why. 

Text Recognition: 

Text Analytics Solutions can assist with deciding grammatical features as well as genuine elements. For instance, the grammatical form might be a thing, however data mining will separate whether that thing is an individual or a spot. 

Text Extraction Tool: 

Another significant component of text analytics is text extraction solution, which permits clients to decide examples and topics inside content. 

Sentiment Analysis: 

These highlights at last lead to sentiment analysis. Sentiment analysis tool can present slant investigation scores, deciding whether the content is certain, negative, upbeat, miserable, or nonpartisan, among numerous different characterizations.

Conclusion

Hope this article helps you to find the best text analytics solution provider which suits your organization. And your feedback is always welcome through the comment section.

Thanks and Regards,
Priyamvadhan

teX-Ai - Ai based Text Analytics Tool