Long gone are the days when organizations were dependent on IT teams for Business Intelligence reporting. Back then, IT teams typically had to adjust data models to facilitate specific questions upfront, were exceedingly slow to change models for any additional questions, and made users wait weeks and months for insights from stale, historic data.
Today, BI reporting is almost exclusively self-service, due in no small part to the influence of Natural Language Generation. Adding NLG to myriad BI tools is integral to generating narratives about the import of data to specific business objectives. Moreover, it supports ad-hoc questions and, when implemented in the proper solution, underpins conversational AI interactions with datasets for unparalleled perceptivity into data’s significance for next best actions.
“NLG does this robotic task of writing reports so you can free up your experts on more valuable tasks,” explained Bryan Zwahlen, Arria NLG Senior Vice President of Customer Success and Partner Relations. “This gives you the ability to write reports more frequently, perhaps, and write more reports so you can actually scale throughout the organization…so you can have that speed to information.”
Viewed from this perspective, NLG is the foundation for increasing data literacy, fostering conversational AI, and exploiting innovative reporting channels for timely insight.
The Worth of Data Literacy
By enabling organizations to improve data literacy throughout their organizations, NLG is instrumental in democratizing the ability to engage in self-service reporting for BI and other needs. In that respect, NLG is a critical tool throughout the data ecosystem because of its enablement of the numerous capabilities data literacy reinforces.
“If people are data literate, they learn how to ask the right questions of the data,” noted Arria NLG Chief Product Officer Ross Turner. “They’re empowered to better interpret the results and understand analysis. They’re better enabled to test their hypothesis they have around the data and, ultimately, communicate clear and coherent stories to stakeholders.”
Trustworthy NLG solutions cultivate data literacy by creating transparency around where data stem from, how they’ve been collected, and eliminating the silo-based culture that otherwise impedes the progress of organizations.
NLG technologies aren’t just responsible for translating numerical and statistical data into natural language summaries laymen users can understand. The best of these solutions actually analyze data to then derive this sought out information as insights. These traits are foundational to the sort of self-service BI reporting that allows users to optimize the value of data analytics.
“Having a self-service mentality is another important enabler of data literacy,” Turner reflected. Moreover, the underlying stories or narratives provided by NLG in BI and other reporting use cases are critical to discerning exactly what data indicate about business problems.
“Narrative is the communication and context piece of data literacy,” Turner noted. “So, as a natural way for people to communicate, it provides instant understanding of data to users, and Natural Language Generation is really a technology enabler that allows the integration of narrative into self-service reporting.”
Innovative Reporting Channels
Firms can maximize the merit of self-service BI reporting supported by data literacy with what’s becoming known as innovative reporting channels: a confluence of conversational AI, BI dashboards, and digital virtual assistants. The synthesis of these capabilities lets users have real-time conversations with bots or agents that access backend reporting systems to issue rapid results of data analytics via speech.
The conversational aspect of this approach is formidable. It’s effectively hands-free, provides insights without cumbersome computer screens, and is ideal for working remotely or in mobile situations. There aren’t too many better ways to engage busy executives, business analysts, or any other type of end user than by allowing them to simply engage in conversations with their data, about their data.
Making the Most of Reporting
This conversational style of reporting symbolizes the ultimate democratization of data literacy while equipping organizations with the foundation they need to truly exploit the reams of data at their disposal.
Additional benefits include the fact that it “relieves people from trying to do interpretation of results by themselves by raising the self-service mentality and making data and information available, basically,” propounded Stephan Schussler, Senior Manager of Intelligent Automation and NLG Lead, Deloitte Consulting. “It’s not about data; it’s about the information inside the data that’s available to all the people who need this information to make decisions.”
NLG, conversational AI, and innovative reporting channels provide those capabilities so organizations can maximize the value of reporting.
Featured Image: NeedPix
Jelani Harper is an editorial consultant servicing the information technology market. He specializes in data-driven applications focused on semantic technologies, data governance, and analytics.