Data Warehousing and Data Mining (DWDM)

 

Module Outline

Week

Topics

1

Data warehousing requirements.

2

Data warehouse conceptual design.

3

Data warehouse architectures.

4

Data warehouse logical design: star schemas, snowflake schemas, fact tables, dimensions, measures.

5

OLAP architectures, OLAP operations, SQL extensions for OLAP.

6

 

Data warehouse physical design: partitioning, parallelism, compression,

indexes, materialized views, column stores.

7

Data warehouse construction: ETL and refresh…

8

Data warehouse architecture trends. MapReduce and warehouse architectures: Pig, Hive, Spark.

9

Data mining concepts, tasks and algorithms.

10

Data mining technologies and implementations…

11

Research trends in data warehousing and data mining.

 

 

Copies of Notes

 

Copies of notes and other resources can be accessed from Moodle and:

            http://www.dcs.bbk.ac.uk/intranet/r/modules/dwdm/

 

Coursework Exercise

 

Deadline - 18 March 2018

Assessment

 

By 2-hour written examination summer 2018 and Coursework Exercise weighting 90% and 10% respectively.

Reading

 

R. Ramakrishnan and J. Gehrke, Database Management Systems Third Edition, McGraw Hill, 2003, ISBN 0-07-246563-8:

http://www.cs.wisc.edu/~dbbook

 

M. Golfarelli and S. Rizzi, Data Warehouse Design: Modern Principles and Methodologies, McGraw Hill, 2009, ISBN 978-0-07-161039-1:

http://www.mhprofessional.com/product.php?isbn=0071610391

 

J. Celko, Joe Celko's Analytics and OLAP in SQL, Morgan Kaufmann, 2006, ISBN 978-0-12-369512-3:

http://my.safaribooksonline.com/book/databases/sql/9780123695123

 

J. Han and M. Kamber, Data Mining Concepts and Techniques (3rd ed), Morgan Kaufmann, 2011, ISBN 978-0-12-381479-1:

http://www.elsevierdirect.com/v2/companion.jsp?ISBN=9780123814791