In this era of information world, given any topic, we are able to get relevant data or documents at a mouse click. The flexibility that internet provides is the user friendly language or Natural Language to search for required topic. Natural Language Querying and Retrieval has made internet popular. It is implicit for business user to understand what the business data is indicating to find better business opportunities. Querying for required data the business users are using SQL. To effectively Query such systems, the Business users has to master the Language. But many business users may not be aware of the SQL language or may not be aware of the databases and some users feel difficulty to write the long SQL Queries. Therefore, it is equally important to query the database very easily. The work here presents a case study to help the business users to type a query in Natural Language, which then converts into SQL statement and process this SQL query against the Databases and get the expected result. This work proposes QCNER approach to extract SQL properties from Natural Language Query. The proposed approach after the application of SMOTE technique depicts 92.31 accuracy over the existing models.1