4 Ways Natural Language Generation Advances BI
Advanced NLG is a subfield of AI that uses advanced analytics to identify what’s important in data, then transforms those insights into intelligent narratives.
Join the DZone community and get the full member experience.Join For Free
There’s been lots of buzz lately in the business intelligence (BI) world about using chatbots and conversational agents like Alexa to further interact with data and visualizations. In order to separate hype from reality, it’s important to understand what is going on under the hood in order for these systems to facilitate valuable conversations.
To move from a simplistic Q&A with your data to an engaging, intelligent conversation that uncovers drivers of business performance, it is necessary to power your bots and agents with advanced Natural Language Generation (NLG). Advanced NLG is a subfield of artificial intelligence that uses advanced analytics to identify what’s important in data, then transforms those insights into intelligent narratives: automated, actionable, human-sounding stories at machine scale. Pairing advanced NLG with BI creates endless possibilities for accessing actionable information anywhere, anytime.
4 Ways NLG Advances BI
Here are four ways the NLG advances BI.
1. It Enables Smart Data Discovery
It enables smart data discovery by identifying trends, correlations, and anomalies not obvious by looking at data or visualizations along by automating advanced analytics that highlight what matters most. By instantly transforming charts and graphs into intelligent narratives, you get a deeper understanding of what is going on in your business.
2. It Makes BI More Accessible
It makes BI more accessible by communicating insights in conversational language. With the amount of data at our fingertips growing exponentially, more and more users are leveraging BI to make important decisions. However, not everybody is a trained expert in data analysis. By pairing visualizations with data-driven narratives, everyday users no longer need to know how to interpret sophisticated charts and graphs and explain key takeaways. The misinterpretation of insights is reduced, as everyone gets a consistent, objective analysis of the facts within the data.
3. It Saves Users Time
It saves users time by automating routine analysis. Imagine if you spent hours each week analyzing data and writing reports that communicate the analysis for others. By integrating advanced NLG into your BI environment, you could create those reports in mere seconds at extraordinary scale and accuracy. When a machine automates the more routine analysis and communication tasks, productivity increases and employees can focus on more high-value activities.
4. It Powers Conversational Systems
It powers conversational systems that deliver insights anywhere, anytime. By infusing advanced NLG into conversational systems such as Amazon Alexa and chatbots, these systems move beyond shallow Q&A experiments to truly intelligent partners that communicate the most relevant insights within your data and visualizations. This way, you can understand drivers of business performance wherever you are, without needing to pull up a dashboard. Whether you are at home, in the office, or simply on the go, ask — or type — your business questions and receive intelligent answers in real-time.
“Natural Language Generation dynamically increases the volume and value of insights and context in data analytics. It automatically generates a specialized narrative for each user in context, to explain meaning or highlight key findings.” — Gartner, Top 10 Technology Trends in 2017, October 2016
Published at DZone with permission of Shelby Blitz, DZone MVB. See the original article here.
Opinions expressed by DZone contributors are their own.