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IASD Master: Data acquisition, extraction, and storage

The objective of this course is to present the principles of the knowledge discovery and data mining pipeline, covering acquisition, storage, and extraction. From storing data to searching for similarities, the course will include a mix of lectures and practical sessions.

Lectures:

Each lecture has two 1.5 h parts (with a 15 min break in between), starts at 9 am and ends at 12.15 pm.

Session	Title	PDF	Exercices
Sep. 18	Introduction: data acquisition and searching the web		Ex1: Ex2:
Sep. 25	Data storage: from hardware to databases
Oct. 02	Foundations of relational and non-relational databases
Oct. 09	Handling complex data: document and graph databases
Oct. 16	Data extraction: foundations of similarity search
Oct. 23	Multi-dimensional similarity search
Oct. 30	Exact versus approximate search
Nov. 06	Conclusion: beyond similarity-based query

Final Exam (50% of the final grade)

This exam lasts 2.5 h. The only documents allowed are 6 handwritten A4 sheets (both sides). Communicating devices are strictly forbidden. When writing code, imprecision in language syntax will be tolerated. The exam is graded out of 20 points. The questions will cover Lectures 1 (Sep. 18) to 7 (Oct. 30). There is only one bonus question on Lecture 8 (Nov. 06).

Session	Type	PDF
Dec. 01	Written exam of 2.5h

Practice Sessions (50% of the final grade)

This course has two practice sessions covering both database systems (Lab 1) and Similarity-based algorithms (Lab 2). Each practice session is divided into Part 1, tackled in Class, and Part 2, to do as homework. The notebook, with code, results, and explanation, should be filled out (for both Part 1 and Part 2) and sent to me by email in both PDF and IPYNB formats (at paul [dot] boniol [at] inria [dot] fr) before the corresponding deadline (at 5 pm CEST (Central European Summer Time)). Each Practice session is graded out of 20 points.

Session	Title	topic	Notebook	Data	Deadline
Oct. 09	Database of documents				Oct. 22
Oct. 23	Similarity Search				Nov. 05

External Resources

This course is highly inspired by previous courses of other professors and researchers listed below:

Author(s)	Title	Link
Pierre Senellart	Data acquisition, extraction, and storage (2025–2026)
Philippe Rigaux	BDpedia
Themis Palpanas	Time Series Management
R. Behmo, N. Travers	Openclassroom NoSQL course
Maude Manouvrier	SQL,NoSQL,NewSQL
A. Silberschatz, H. F. Korth, S. Sudarshan	Database System Concepts