Big Data for Marketing

Objectives

1. Introducing the students to the concept of Big Data
2. Making them familiar with the most used technologies for handling a vast amount of data
3. Understanding a program written with the Map-Reduce logic
4. Being able to perform ETL tasks on a vast amount of data
5. Storing and retrieving data stored in the Hadoop file system
6. Executing query on a non SQL database
7. Applying the concepts learnt in the field of Marketing
8. Solving a business problem characterized by a vast amount of data

General characterization

Code

200202

Credits

7.5

Responsible teacher

Docente a designar

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

Bibliography

- White, T. (2012). Hadoop: The definitive guide. " O 'Reilly Media, Inc.".
- Karau, H., Konwinski, A., Wendell, P., & Zaharia, M. (2015). Learning spark: lightning-fast big data analysis." O'Reilly Media, Inc.".
- Leskovec, J., Rajaraman, A., & Ullman, J. D. (2014). Mining of massive datasets. Cambridge university press.

Teaching method

Evaluation method

Subject matter

1. Introduction to Big Data
2. The five V of Big Data
3. The Hadoop file system
4. Using Map-Reduce for writing Hadoop Programme
5. The Map Phase: how to organize the data
6. The reduce phase: techniques for combining data with a common key
7. ETL with Sqoop
8. Differences Between SQL and non-SQL languages
9. Running a query on a vast amount of data
10. Technique to optimize a query in a production environment
11. Applications of the different tools to address complex tasks

Programs

Programs where the course is taught: