Augmented Analytics and Tableau

Traditionally, business intelligence tools are complex and difficult to navigate. Furthermore, they are visually driven which means that analysts or the end consumer still has to create his own story and insights from the dashboards.

Augmented analytics is the next wave of analytics that seeks to automate insight discovery and data preparation through artificial intelligence. Rather than replace humans like traditional AI technologies such as RPA, Augmentation seeks to improve human decision making. Augmented analytics is a kind of augmented intelligence technology based on cognitive computing that seeks to improve and augment the human analysts working on various dashboards and business intelligence tools.

Introduction

Traditionally, business intelligence tools are complex and difficult to navigate. Furthermore, they are visually driven which means that analysts or the end consumer still has to create his own story and insights from the dashboards. Augmented analytics seeks to bridge this gap by providing deep insights in natural language text for a higher impact delivery.

BI Tool

One of the leading business intelligence tools, Tableau which is also featured in Gartner’s magic quadrant recently made a foray in augmented analytics. As the industry gradually moves beyond traditional visualisation based analytical tools, companies are looking at new sources of augmentation through AI. NLP and NLG plays a critical role in augmented analytics as it allows business users easy access to dashboards while increasing BI adoption across the enterprise.

Tableau’s ask data is one such example of BI tools incorporating NLP in order to simplify the entire analytical journey. Users can ask questions which are semantically broken down into keywords.

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