Querying in Natural Language opens up corporate Databases to non-technical business users
Business efficiency and overall business productivity depends on the speed and quality of the decisions that the business users and executives make. Business executives and business users make operational decisions using data they access from corporate databases.
However, one significant hurdle persists: databases that store the data require employing cryptic query languages and elaborate BI applications to access the data. Business users lack the skills to use the query languages or the training needed to engage the BI applications.
Typical corporate databases support different query languages: SQL, SPARQL, Graph QL, OData APIs, etc. But, the steep learning curve discourages especially the business users from using these query languages, resulting in inefficient and often incomplete exploration and analysis of data leading to poor decision processes.
