Natural Language Processing & Conversational Analytics

All kind of industries generate and collect an unimaginable quantity of data nowadays. According to an IDC report, the amount of data will grow globally from 33 zettabytes (33 trillion gigabytes) in 2018 to 175 zettabytes in 2025. Unfortunately, even large companies with huge budgets and big teams are already facing many unresolved challenges regarding the processing, evaluation, and efficient use of these huge amounts of data. The US analysis and consulting company Gartner, well- known for its in-depth studies such as the “Magic Quadrant” or technology forecasts like the “Hype Cycles”, provides some seminal solutions for these challenges and ‘Natural Language Processing’ (NLP) and ‘Conversational Analytics’, our topics of the month, play an important part here.

Natural Language Processing (NLP) is a branch of linguistics and computer science that deals with the interactions between computers and human (natural) languages. Currently, companies are particularly concerned with the question of how to program computers to process and analyze large amounts of natural language data. This applies to search engines, voice commerce, voice assistants as well as analytics applications, especially since Gartner claims that 50% of analytics queries will be generated in systems via search, voice input (NLP) or automatically this year. The end customer trend of voice control in the car, for instance, via smartphone or smart speaker, is indeed getting more and more popular in B2B analytics applications. Hence, it is predicted that already by next year, processing natural language will increase acceptance of analysis and business intelligence software from 35% of employees to over 50%. This will make analytics more usable for new user groups such as managers, salespeople, or creative people. Such NLP functionalities are offered, for instance, already by companies like Qlik or Tableau.

Commercial AI & ML

Currently, many popular Artificial Intelligence (AI) and ...