NLP provides any user with an easier way to ask questions about data, as well as receive an explanation of rendered insights. Natural language query (NLQ) approaches to asking questions of data enable data and analytics access to mainstream business users. Conversational analytics is still emerging but takes a step further by allowing questions to be posed verbally. This voice interaction could be through a digital assistant (such as Amazon Alexa). In addition to voice support for queries, these capabilities are emerging to be conversational in the form of a virtual AI assistant or bots.

By 2020, 50% of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.

Gartner Predicts

What does NLP & Conversational AI Enable?

  • NLP/conversational analytics brings ease of use to a new level, and allows a query to be as easy as a Google-like search or a conversation digital assistants, such as Alexa.

  • The combination of NLP with augmented analytics — including automatic insight generation — allows users to rapidly find the proverbial needle in a haystack, presenting the most-important and actionable insights via conversational analytics with natural language generation.

  • More-robust NLP interfaces include industry or domain-specific taxonomies and linguistics (such as HR, finance, healthcare or financial services) so that phrases are more correctly interpreted.

  • NLP and conversational interfaces are being embedded in analytics and BI platforms, digital personal assistants, chatbots and applications.

  • NLP provides intuitive forms of communication between humans and systems.

  • NLP and underlying knowledge graphs are being extended to analyze unstructured and other data types, and used as a foundation for data science as well as ML/AI models.

How Does This Impact Your Organization and Skills?

  • Conversational analytics can dramatically improve the adoption of analytics by every employee, rather than by predominant power users and business analysts, resulting in higher business impact.
  • However, as access to more powerful insights permeates the organization at all skill levels, there is a need for a formal and enterprisewide focus on improving the data literacy of all users.

We've got you covered!

Relevant Sessions

  • The Foundation of Modern Analytics and BI
  • Five Best Practices for Real-Time Analytics and Continuous Intelligence
  • How to Improve Your Organization with Business-Domain-Focused Data and Analytics
  • The Future of Analytics and BI: The Augmented Consumer
  • Storytelling for AI-Leads, Data Scientists & Machine Learning Engineer

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