Big Data

Databases
Data Structures
SQL

Classes:
1. Theoretical exposition of the Big Data foundations
2. Theoretical exposition of Big Data processing technologies
3. Application examples/exercises

On successful completion of this course unit, the student should be able to:
1. Known and understand the principles and concepts of storage, processing and analysis of Big Data.
2. Identify and apply the concepts and storage techniques, processing and analysis of Big Data to solve practical problems.

1. Introduction to Big Data
– New generations of databases
– What is Big Data?
– Characteristics of Big Data
– Domain Specific Examples of Big Data

2. Big Data in Sustainable and Smart Cities
– Sustainable and Smart Cities: reference models and challenges
– Data analysis
– IoT for Sustainable and Smart Cities of the future
– Impact, challenges and opportunities of Big Data in cities.
– Big data applications for smart cities.

3. Big Data Processing
– Limitations of traditional systems
– Data storage systems
– Distributed processing frameworks
– Big Data Platforms
– Data processing tools and techniques

NAO

• Lim, C., Kim, K.-J., & Maglio, P. P. (2018). Smart cities with big data: Reference models, challenges, and considerations. Cities, 82, 86–99. https://doi.org/10.1016/j.cities.2018.04.011.
• ‌Osman, A. M. S. (2019). A novel big data analytics framework for smart cities. Future Generation Computer Systems, 91, 620–633. https://doi.org/10.1016/j.future.2018.06.046.
• ‌Hashem, I. A. T., Chang, V., Anuar, N. B., Adewole, K., Yaqoob, I., Gani, A., Ahmed, E., & Chiroma, H. (2016). The role of big data in smart city. International Journal of Information Management, 36(5), 748–758. https://doi.org/10.1016/j.ijinfomgt.2016.05.002.
• ‌‌Maribel Yasmina Santos. (2020). BIG DATA : concepts, warehousing, and analytics. River Publishers.
• ‌Erl, T., Khattak, W., & Buhler, P. (2016). Big data fundamentals : concepts, drivers & techniques. Prentice Hall ; Vancouver, Bc.
• ‌Arshdeep Bahga, & V Madisetti. (2016). Big data science & analytics : a hands-on approach. Arshdeep Bahga & Vijay Madisetti.
• Provost, F., & Fawcett, T. (2013). Data science for business : what you need to know aboout data mining an data-anal. O’reilly.
• Bengfort, B., & Kim, J. (2016). Data Analytics with Hadoop. O’Reilly Media, Inc.
• White, T. (2015). Hadoop: the definitive guide: storage and analysis at internet scale. Beijing O’reilly Media.