News

28-10-2017 The first lecture :)

The aim and the scope of the course

The aim of the course: To get to know how to design and construct data warehouses for efficient data processing.

The scope of the course:We will learn about:

Information about the Course

Schedule of Lectures

29-10-2017Introduction [pdf]
29-10-2017Evolution of database systems [pdf]
18-11-2017Dimensional modeling [pdf]
18-11-2017ETL and OLAP systems [pdf]
26-11-2017MapReduce in Spark [pdf]
14-01-2017Processing of very large data [pdf]

Schedule of Labs

18-11-2017 Dimensional modeling [pdf] [report-1.pdf] [report-1.tex]
25-11-2017 Data transformation [pdf] [unique_tracks.zip] [triplets_sample_20p.zip] [report-2.pdf] [report-2.tex]
16-12-2017 MapReduce in Spark [pdf] [all-shakespeare.zip] [matrix M] [vector x] [vector v] [unique_tracks-csv.zip]
21-01-2018 MapReduce in Spark: Matrix multiplication [pdf] [data for matrix multiplication]

Evaluation

Lecture:
Test : 75 points (min. 50%)
Labs : 25 points (min. 50%)
Labs:
Regular tasks and exercises : 4x25 points (min. 50%)
Bonus points for all: up to 10 points.

Scale

90% 5.0
80% 4.5
70% 4.0
60% 3.5
50% 3.0

Bibliography

Z. Królikowski, Hurtownie danych: logiczne i fizyczne struktury danych, Wydawnictwo Politechniki Poznańskiej 2007

R. Kimball, M. Ross, The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, John Wiley & Sons 2002

A. Rajaraman, J. D. Ullman, Mining of Massive Datasets, Cambridge University Press, 2011, http://www.mmds.org.

H. Garcia-Molina, J. D. Ullman, J. Widom, Systemy baz danych. Kompletny podręcznik. Wydanie II Helion, 2011.