Natural Language Understanding and Augmented Analytics

The transitional way to let computer understand human intent, and follow us to finish a set of instructions, is to write codes, like Java and C, as a strictly defined format of input to the computer. Currently, with the development of Natural Language Understanding(NLU), the computer is more and more intelligent to comprehend human’s intent. NLU enables computers to understand human without formalized syntax of programming languages and to communicate back to humans in natural human languages.
The filed of NLU is an important and challenging subset of natural language processing(NLP). While both understand human language, NLU is tasked with communicating with untrained individuals and understanding their intent, moreover, understands the meaning of human in spite of errors of mispronunciations or transposed letters or word are made.

NLU uses algorithms to reduce human speech into a structured ontology, therefore it can interact effectively with the public without supervision. That’s why NLU is warmly welcome in many start-up companies and major IT companies. Besides bringing a better and more convenient interaction between human and computer, NLU enables the development of very advanced and potential technology in modern time, for example, Augmented Analytics.

Augmented Analytics is kind of a new item that has been hotly discussed in the data analytics summit at the beginning of 2019. Some famous expert data scientists predicted it to be one of the most powerful technologies in the coming several years. It will become the significance in next wave of disruption because it is changing the previous data analytics by using machine learning and AI in BI tools to automate data preparation and help users discover and share insights more easily. It is one main purpose of Augmented Analytics to enable non-data scientists or citizen data scientists to approach advanced analytics techniques to discover chances from massive data sources, solve more complicated problems and better optimize outcomes.

With the ability of computer program to understand to informal human language as it is typed or spoken out loud, NLU makes analytics tools as easy as search interface or a conversation with a virtual assistant, it is estimated that half of the analytical queries will be generated by either search, NLU or voice or automatically by AI software.

The need to make analytics accessible to everyone in the organization is driving adoption of the trend, By 2021, NLU and conversational analytics will boost analytics and BI adoption from 35% of employees to over 50%.
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