Class Datawarehouse Techniques

This course intends to give an introduction to Data warehouse Topics and its evolution to date.

This course aims to introduce the motivations of the need for the data warehouse in its original and functional perspective and with the advent of big data what are the challenges that the data warehouse has faced for its evolution and purpose.

This course provides not only an introduction to data warehouse topics but also the introduction of new paradigms and solutions that complement the present day (big-data) function and objectives of a data warehouse. Thus introducing other themes such as Data Vaults, Data Lakes and technologies such as Hadoop with Map Reduce (storage and recall) and others such as Spark (memory based).

This Curricular Unit complements and integrates itself, thus, to the present cycle of studies offering a disciplinary component of data warehouse and its evolution.

PC1: Operating Systems, operational data and OLTP (OnLine Transactional Processing) and the need for strategic information.

PC2: Strategic Information and the need for a new system, data warehouse. Requirements to have a data warehouse and its components. The why and the inability of OLTP operating systems to handle Strategic Information.

PC3: Data Warehouses as a solution for storage, management and manipulation of strategic information and main differences with operating systems.

PC4: Introduction to the various stages of the data warehouse: Data (e.g. OLTP) - Extract Transform Load - Data storage - Data Analytics (BI, Data Science and Hadoc Reporting) and Data warehouse management.

PC5: Data Warehouse Architecture. The various types of architectures for a data warehouse (Top-down and Botton-up and others).

PC6: OLAP systems, hyper-Cubes and Cube operations.

PC7: Beyond Data Warehouses: Big data, Data Vaults, Data Lakes Hadoop / Map Reduce and Spark systems.

The subject has a strong practical component where students have to apply knowledge and obtain visible results.

• Ponniah, P. (2010). "Data Warehousing". Second Edition. Wiley. New Jersey.
• Kimball, R., Ross, M. (2013). "The Data Warehouse Toolkit". Third Edition. Wiley. Indiana.