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What is Clickless Analysis and Why Should I Care?

Natural Language Processing Makes Search Analytics Easy!What is Clickless Analysis and Why Should I Care?

Whether you know it or not, you know Natural Language Processing (NLP) very well! You use it all the time to ask questions on Google Ask a simple question, get a list of responses that meet your needs. What did we ever do before natural language processing? How else might we use it to simplify our lives?

Search Analytics uses NLP in lots of ways today. And, one of the most valuable ways we can use Natural Language Processing in search analytics is to use it in the practice of analytics itself! With the simplified process of asking a question in an analytical solution, your business can provide advanced analytics to your business users and let them use their business knowledge and skill to find and analyze information in a simple way that is meaningful to their role and their objectives.

Let’s talk about Clickless Analytics, shall we? What is Clickless Analytics? It is the method used to find, analyze and visualize data without having to write queries or understand programing knowledge or data science. What is Clickless Analysis? It is analysis that does not require endless clicking and choices. Instead, your users can enter the information in natural language and enjoy a seamless Augmented Analytics and advanced data discovery solution that uses machine learning and natural language processing (NLP), in a self-serve environment to democratize advanced analytics. In other words, no advanced training is required!

If you want to give your business users Advanced Analytics Tools that are easy to use, Contact Us to see how easy Clickless Analytics can be and how your business users can become Citizen Data Scientists.

Original Post: Natural Language Processing Makes Search Analytics Easy!



This post first appeared on Business Intelligence, Corporate Performance Management, please read the originial post: here

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What is Clickless Analysis and Why Should I Care?

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