Guided Natural Language Query

Providing your analytics users the ability to get answers from their data is useful, but only if the solution can guide them to ask the right questions.

While self-service analytics is typically a key goal for modern organizations to derive more answers from data, only two out of five (40%) report their analytics users can analyze data without help from IT, according to Ventana Research.

To help those without training better analyze data, tools like natural language query (NLQ) allow you to ask questions of your data, receive a best practice chart or report that answers your query, and provides a deeper level of understanding.

NLQ tools typically come as a free text search bar with limited reactivity or guidance provided for the user to help build their question. However, the latest type, Guided Natural Language Query, extends its potential by taking a guided approach to self-service BI. Yellowfin Guided NLQ is our exclusive and native NLQ tool that helps your users build their data question by automatically and dynamically generating suggestions on how to pose it, step-by-step. With its additional AI NLQ mode, Guided NLQ can also use generative AI to automatically structure the question on the behalf of the user, allowing anyone to type any question in true natural language.

Guided NLQ ultimately acts as a simpler way for anyone of any skill level to explore their data, and get more relevant answers - and provides a number of key benefits.

In this free whitepaper, we explain:

• What Guided NLQ is - and the other types of natural language query
  
• How Guided NLQ works - with examples
  
• Why it will provide true self-service BI for everyone - through 5 key benefits
  
  

This  guide will assist you in understanding the benefits of Guided NLQ and its significant impact in opening up true self-service BI for everyone - not just analysts.