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Text Mining Vs Text Analytics

During the initial stages of development of analytics technologies, Big Data processing used to be a lot of time consuming process. Even implementing the algorithms in Machine Learning models used take a lot of time.  It was only after the advent of advanced tools like Hadoop, Azure, KNIME along with the other big data processing software’s that Data Scientists were able to process Big Data more rapidly & efficiently.

The advent of such high performance tools & software’s has made the life of Data Scientists a lot easier. With a lot of time being saved, Data Scientists have then started setting their focus towards working on the other advanced analytics concepts. It was at this time that text mining & text analytics have gathered a lot of prominence.

Text Analysis-

Text analysis can be interpreted as automated analysis of unstructured textual data, containing within it the methodologies of text mining and text analytics. At the present time, analytics experts make use of several advanced techniques for text analysis like Sentiment Analysis, NLP models, Information Extraction, and Document Categorization and more

Text Mining-

Text Mining has also gained a lot of prominence over the years. Enterprises these days have started using text mining at large so as to extract valuable inputs from the text available. To explain this simply, let’s consider the example of product based companies. They can make use of the twitter data/ Facebook data to accurately analyze the performance of their products among their customers by implementing Text Mining along with Sentimental Analysis.

Differentiating Text Mining vs Text Analytics-

  • Meaning

Text Mining- It can be defined as the process of collecting & preparing the data for text analytics

Text Analytics- It can be defined as the process of implementing statistical & Machine Learning models to extract the insights & to accurately predict from the data which is pulled through text mining.

  • Framework

Text Mining- It makes use of ETL framework

Text Analytics-it makes use of advanced frameworks like LearnSec

  • Programming Languages

Text Mining-R & Pythonare among the most commonly used programming languages for text mining.

Text Analytics-If the data is made ready to be analyzed then we can go with any of the available analytics software including R & Python along with PowerBi, Azure and more.

In order to obtain better performances it is advised to use text analytics with text mining combined.

If you wish to excel in career as a Data Scientist then having hands-on knowledge of both text mining & text analysis is very crucial. Be a part of our Analytics Path advanced Data Science Training in Hyderabad & gain complete hands-on knowledge of text mining & text analytics with the application of real-time projects.

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