Business intelligence and analytics platform vendors are now providing augmented analytics capabilities that empower citizen data scientists. Specifically, they use natural language understanding capabilities to enable natural language searches and deliver the results using natural language generation. The result is a "conversation" between the user and the system. Augmented analytics tools also come with pre-built machine learning models to empower any user to do single click forecasts, identify trends and trend reversals, anomalies, outliers -- tasks that in the past required involvement from professional data scientists. In short, the opportunities are many, but many enterprises have a way to go before their businesses are truly "insight-driven."

Organizations have been using natural language processing (NLP) for text analytics to identify patterns in data such as social media sentiment and contract review, but NLP usage has been expanding. "The big change that's happened in the last five years is the amount of context and understanding that can be extracted or used when understanding documents," said Nigel Duffy, global artificial intelligence leader at EY. "Our ability to understand information from documents is much, much greater than it was a few years ago." BI and analytics vendors are adding NLP capabilities to their products such as natural language generation for data visualization narration and natural language understanding for natural language searches. In doing all of this, they're making data visualizations easier to understand and their products easier to use. For example, Tableau, Sisense, and Qlik have all partnered with Narrative Science to narrate data visualizations with text.