Arria hosted a new and well-attended webinar last Thursday, November 14, to discuss how two pivotal technologies—Natural Language Generation and Robotic Process Automation—can work together to expedite the flow of information within businesses. Because of the groundswell of interest, we have added the subject to our regular rotation of webinar topics. To register for the next NLG+RPA webinar or any other session, visit our webinar registration page. In the meantime, here are some key takeaways.
NLG performs the amazing feat of giving machines the power of human language. In doing so, it offers a quick route to ROI and pushes forward the democratization of data literacy—particularly in the areas of FP&A, operational analysis, BI, and almost any task that involves RPA. Here we’ll offer an overview of key points for executives who are considering NLG as a component of their overall automation strategy.
DevPro Journal published an article this week entitled "NLG: Bridge the Communication Gap Between People and IT," based on an interview they recently conducted with Arria COO Jay DeWalt.
The article establishes that Natural Language Generation (NLG) is a separate layer of the natural language technologies stack,
We were pleasantly surprised at Arria to see this spontaneous case study developed and published by Analytics Insight. In "Arria helps a multinational corporation automate business intelligence process for quick decision-making," the authors make many of the points that we would have made if we had written the article ourselves.
It may at first seem counterintuitive that math plays an important role in daily conversation, but let’s consider how frequently our word selection and sentence composition are supported by mathematical calculations. Then we’ll discuss the implications for Natural Language Generation (NLG)
After our previous post about the groundbreaking work that data reporters at RADAR AI and BBC News Labs are doing to bring attention, context, accuracy, and timeliness to hyperlocal news stories, Gary Rogers, RADAR AI’s CEO, gave us a nice shout out on LinkedIn. Gary called Arria NLG Studio “a great tool in [RADAR AI’s] data-driven workflow
We’ve written about how Natural Language Generation can eliminate the bottleneck of manual, one-at-a-time analysis within business environments, producing data-driven insights that otherwise would remain fossilized in spreadsheets on the network drive. It is also worth noting that the same principles apply to the world of news reporting
Question: “Where does NLG sit in the technology stack?”
Answer: “As the push toward digital transformations gains momentum, maintaining Natural Language Generation (NLG) as a separate layer of the technology stack is ever more critical for ensuring the democratization of data literacy.