A Natural Language and Interactive End-to-End Querying and Reporting System

Natural language query understanding for unstructured textual sources has seen significant progress over the last couple of decades. For structured data, while the ecosystem has evolved with regard to data storage and retrieval mechanisms, the query language has remained predominantly SQL (or SQL-like). Towards making the latter more natural there has been recent research emphasis on Natural Language Interface to DataBases (NLIDB) systems. Piggybacking on the rise of 'deep learning' systems, the state-of-the-art NLIDB solutions over large parallel and standard benchmarks (viz, WikiSQL and Spider) primarily rely on attention based sequence-to-sequence models.