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dc.contributor.author Gohar, Abdullah
dc.contributor.author Tariq, Mishal
dc.contributor.author Younas, Ammar
dc.contributor.author Ayaz, Muhammad Hassaan
dc.contributor.author Supervised by Dr. Naima Iltaf
dc.date.accessioned 2025-02-12T07:04:00Z
dc.date.available 2025-02-12T07:04:00Z
dc.date.issued 2024-06
dc.identifier.other PCS-496
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/49748
dc.description.abstract Data extraction from databases often proves to be a exhausting and time-consuming task, using valuable resources within organizations. These challenges are particularly felt by data and business analysts, whose core responsibilities may be sidelined by the demands of database interaction by non tech department. DataDialogue focuses to streamline the user-database interactions. Using advanced and latest techniques, including but not limited to Large Language Model (LLM) and Langchain, alongside prompt engineering, our solution allows users to effortlessly chat with their databases using natural language without the knowledge of SQL. DataDialogue translates these queries into structured commands (sql queries), executing them seamlessly in the backend. The resulting output is presented in natural language on the frontend. Thus, bridging the gap between users and databases with efficiency and ease. en_US
dc.language.iso en en_US
dc.publisher MCS en_US
dc.title Data Dialogue (DD) en_US
dc.type Project Report en_US


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