4.1.5 Integrating Global Enterprise Data at Scale: AI to the Rescue
Module 4: AI in Practice: Preparing for AI
Asterios Katsifodimos, Assistant professor and Delft Technology Fellow at the Web Information Systems group of the Faculty of Engineering, Mathematics and Computer Science (EEMCS/EWI) at Delft University of Technology explores the use of AI related to the topic of “Integrating Global Enterprise Data at Scale”.
This videolesson is based on scientific studies that are refferred at below. Note: This additional information is not mandatory for the course and is primarily intended for learners who wish to dive deeper into the material:
- C. Koutras, G. Siachamis, A. Ionescu, K. Psarakis, J. Brons, M. Fragkoulis, A. Katsifodimos. 2020. Valentine: Evaluating Matching Techniques for Dataset Discovery. arXiv preprint arXiv:2010.07386 (2020). https://github.com/delftdata/valentine.
- Christos Koutras, Marios Fragkoulis, Asterios Katsifodimos, Christoph Lofi. 2020. REMA: Graph Embeddings-based Relational Schema Matching. SEA Data workshop@EDBT 2020.
AI in Practice: Preparing for AI by TU Delft OpenCourseWare is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at https://online-learning.tudelft.nl/courses/ai-in-practice-preparing-for-ai/ /