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Why Natural Language Processing is the Future of Business Intelligence and Smart Office


Every time you ask Siri for directions, a complex code is activated that allows "her" to understand your question, retrieve the information you want, and then answer your question in a language you can understand. This has become a reality in the last few years. So far, we are still interacting in a language they understand, not in ours. We've learned their business intelligence and smart office language

But now they are learning our business intelligence and smart office language

The technology that supports this change in the human-computer relationship is natural language processing (NLP). It is already changing business intelligence, smart office, which goes much further than mere interaction. Soon, the business world will change and life-changing information will be available just by talking to chatbots.

This future is not far away. You could even say it's right around the corner.

What is Natural Language Processing for Business Intelligence?

Natural language processing, also known as computer linguistics, combines linguistics that allows machine learning, artificial intelligence, and human-computer dialogue.

A few years ago, keywords were combined with "and, or, not" Boolean search terms to perform an effective Google search. To get the answer Google wanted, one had to know the language.

Then Google introduced semantic search. The algorithm learns associations between words, allowing Google to ask questions like a friend. Inside the computer, the question is translated into a Boolean structured search that the computer can understand - but not see the process.

It's you saying to Siri, "What's the weather today?" or "Is the flight to Beijing tomorrow cheap?" It's the same technology as asking. There's no need to modify your English into a computational logic statement.

You just ask Siri. "Which flight to Beijing is cheaper tomorrow?" "I understand," she "says. Siri can understand "tomorrow" and "cheap". There is no need to specify a specific date or define "cheap" as a low price.

These examples are still relatively rudimentary. They are impressive, but they make mistakes. Explain that when they do, your questions should be answered with highly integrated data. The purpose of natural language processing is to deprecate the user graphical interface 3354 or user interface to make interaction with machines easier to talk to people.

This will be a huge offshoot of business intelligence, smart office applications.

Natural language processing will democratize data

In general, the big impact will be to reduce or completely eliminate barriers to business intelligence and high volume data. Many companies in the BI, Smart Office space recognize this trend and have made great strides in user-friendly access and accessibility. But there's still a long way to go.

Imagine the future. Just ask a question and you'll get the answer anywhere, anytime. Convert business intelligence, Smart Office into a conversation with a chatbot and ask, "How were the last three quarters of revenue?" The question is all it takes. "It doesn't take years of experience, familiarity with the software, or worrying about whether the machine will understand the question asked.

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