nBIIG: A Neural BI Insights Generation System for Table Reporting

TL;DR

nBIIG is a neural system that transforms table data into RDF representations and generates fluent textual insights, aiding analysts in creating compelling reports with a human-in-the-loop approach.

Contribution

It introduces a neural BI insights generation system that produces faithful, fluent insights from open-domain tables, trained on curated large-scale data.

Findings

Generates accurate insights over open-domain tables

Utilizes RDF representations for analysis

Supports human-in-the-loop reporting

Abstract

We present nBIIG, a neural Business Intelligence (BI) Insights Generation system. Given a table, our system applies various analyses to create corresponding RDF representations, and then uses a neural model to generate fluent textual insights out of these representations. The generated insights can be used by an analyst, via a human-in-the-loop paradigm, to enhance the task of creating compelling table reports. The underlying generative neural model is trained over large and carefully distilled data, curated from multiple BI domains. Thus, the system can generate faithful and fluent insights over open-domain tables, making it practical and useful.