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Data Warehouses
News
(July 24th 2006) Exam results are now available.
Contents
This course presents the principles of decision support systems and so-called online-analytic processing (OLAP). The course will cover the following topics:
1. Motivation and Architecture
2. Modelling for OLAP: Star Schemas and Snow Flake Schemas
3. SQL Extensions for Decision Support (Cube, Aggregation sets, Pivot, etc.)
4. Demo of a Business Intelligence Tool (BTell)
5. Implementation Techniques (bitmap indexes, materialized views, star joins, ...)
6. Query optimization on virtual databases (federated, heterogeneous databases)
7. Data mining (classification trees, association rule mining, outlier detection)
8. Data cleaning, identity reconciliation
9. Time series, time travel
10. Continuous queries and data streams
11. Probabilistic databases, data lineage
Lecture notes
| Topic | PDF (1/1) | PDF(6/1) |
| Introduction | (1/1) | (6/1) |
| Top N | (1/1) | (6/1) |
| Skyline | (1/1) | (6/1) |
| Query Processing and Indexing (Part 1) | (1/1) | (6/1) |
| Query Processing and Indexing (Part 2) | (1/1) | (6/1) |
| Probabilistic Databases | (1/1) | (6/1) |
| Data Cleaning | (1/1) | (6/1) |
| SAP (Guest lecture by Dr. Kurt Weiss) | (1/1) | (6/1) |
| Data Mining | (1/1) | (6/1) |
| Introduction to Dataspaces | (1/1) | (6/1) |
Exercise Sheets
Exercises 3&4: Query Processing and Indexing
Exercise 5: Probabilistic Databases
Exam
The final exam will take place on Friday, July 7, at 9:15 am in CAB G51. (Same time and place as the lecture.) There will be no midterm exam. No "Testat" is given for this course.
References
Articles of the research literature on databases and information systems (e.g., SIGMOD and VLDB). Exact references will be given in the lecture notes.
Lecturers
Schedule
Language
English
Requirements
ISG (Introduction to database systems, ER/UML modelling, normalization, SQL). Architecture & Implementation of Database Systems course is very helpful.
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