“Think about just how interconnected the world is now,” said Matt Gould, the co-founder of Arria NLG, a prominent enterprise in the development and deployment of Natural Language Generation (NLG) technologies worldwide. “Think about it from just a personal context. How much data are you generating personally every day?

” Modern, connected humans interact constantly online with computers, mobile phones, and many other devices. They pay bills, watch movies, purchase products, interact with medical professionals, use fitness apps, listen to music, and work online.

“That whole drifting miasma of invisible data is spilling off you constantly and consistently, and it’s happening for at least half the world’s population now,” said Gould during a recent DATAVERSITY® phone interview. “Now, the big challenge with that huge generation of data is its synthesis.” Such a synthesis requires understanding to be derived from it in a comprehensible and easily digestible fashion. Take that enormous amount of data coming off individuals and increase it exponentially upwards, and you then reach the amounts of Big Data currently being captured and stored in global enterprises.

The Problem

At this point in the history of Data Management the actual analytics of such vast quantities of data is still quite immature. The Business Intelligence (BI) industry has created a multitude of tools that range from simple descriptive analysis through considerably more advanced prescriptive analysis with such developments as Machine Learning, Data Science, Artificial Intelligence, and others. Such tools can effectively – as long as all the proverbial data ducks are in a row – help aggregate, organize, analyze, and display data into various forms such as visualizations, graphs, dashboards, and the like. But, as discussed in a white paper by Dr. Robert Dale, the Chief Strategy Scientist at Arria NLG, “[C]urrent business intelligence tools, information visualization applications and dashboards only go so far.” It still takes an expert, or in many cases, a meeting of experts to interpret the data in comprehensible ways for people to understand – no matter whether they are marketing analysts, IT specialists, C-level executives, researchers, or consumers. Someone has to sit down, write out an explanation of the data, and be able to present it in a clear format… or put simply, in human language. Gould noted:

What is Natural Language Generation?

One way to answer such a question is to discuss what it is not. According to Gould, “[I]t’s not just templates. It’s a rich narrative, generated from scratch.” He discussed the Google Translate system where a user puts in one language and out comes a similar phrase in another. “It’s amazing,” he said. “And it’s pretty accurate.” The Google system is essentially trying to simulate what the mind does at a very basic level. A user types in a word, phrase, or sentence and the system compares it, looks for nuances in context as best it can, and gives an answer. “But at no point did the system actually know or understand what is being asked of it,” said Gould. “It didn’t need to. It just matched it. That’s what the NLG system does not do… What is does is what your mind does. It starts with a process of data.”

That Arria NLG data process begins with more than thirty years of research and experience from some of the best global scientists in computational linguistics and heuristics, “a whole lot of algorithms,” and numerous technologies and patents within a purpose-built, multilevel NLG engine. Some of them include explicit reasoning, data mining, pattern recognition, space-time analytics, criticality assessment, document planning, sentence aggregation, lexical choice, referring expression generation, linguistic realization, and many others which in the end, according to Gould, turns all that data into written or spoken language, in the same way the human brain does:

“It’s revolutionary in the simplest and most fundamental way. It’s not a self-driving car, it’s not a space robot, it’s not a new kind of battery. It’s so fundamental and natural. We’re giving the Internet a voice, where the Internet can speak to you, generate its own language in real time and not rely on people writing things and storing things for it to reproduce at the right time.”

Actionable Analytics in Human Terms

The business narrative coming out of many cubicles, board rooms, and various staff members puzzling over dashboards and spreadsheets is that there is too much data and it’s too hard to compile all together into meaningful information – data is useless in and of itself. It must become an information asset before real insight is gained. According to Gould:

“Look at what happens when you are a large company and you’ve spent millions, literally millions on CRM systems and ERP systems, stock control systems, and point-of-sale systems, to make it as efficient as possible to manage your business. You’ve integrated all these systems, or you hope you have anyway, and that has cost you a lot. Now the system is reporting to you on the health of the entire system. It knows what is going on; it knows what is happening from the factory floor to the supermarket shelf or Internet web page.”

Src:http://www.dataversity.net/