Project
Profiling of Hybrid Data Lakes
Objective
Hybrid data lakes enable joint querying across structured and un-structured data, but provide no guarantees that the two modalities are complete, aligned, or representative of each other. This work introduces profiling metrics that make these hidden integrity failures explicit and measurable.
Outcome
Expected outcomes include a data quality quantification tool and a potential publication.
| Apply By Date |
15 Feb 2026 |
| Students |
0 / 2 |
| Duration |
4 months |
| Mentor |
Manish Kesarwani |
Tools-Technologies | Jupyter Python Notebooks |
College | All College |