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Learning objectives
Upon completion of the course, the students should be able to understand and cope successfully with various aspects of data management in modern database systems. Emphasis will be given in managing data that have complex structure, such as, text data, web data, social data, etc. Algorithms for approximate query answering and scalable data processing will be studied. The students will also have the opportunity to study platforms for managing big data, such as, map-reduce, platforms for data streams, and platforms for graph data.
Course content
- Structured data, relational databases, algorithms for query optimization.
- Semi-structured data, document-databases, semi-structured data abstraction, representation, and search.
- Unstructured text. IR systems, document retrieval and ranking.
- Platforms for Big Data, algorithms for Map-Reduce & Hadoop,
- Platforms for Big Graphs, algorithms for large graphs.
Textbooks
required
- Database management systems / Raghu Ramakrishnan, Johannes Gehrke / 3rd Edition / 0-07-246563-8 / 0-07-115110-9 (ISE)
Learning Centre : 9 copies for borrowing and 1 for short loan
Computer Science library 2 copies for borrowing and 1 for short loan - Learning Spark: Lightning-Fast Big Data Analysis / Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia / O'Reilly Media; 1st edition / ISBN-13: 978-1449358624 / ISBN-10: 1449358624
In Safari as an e-book with 3 users licence
In EBSCO as an e-book with one user licence
Learning Centre : 1 copy for short loan and 1 coursebook for borrowing
Computer Science library : 1 copy for short loan and one coursebook for borrowing - Data on the Web: From Relations to Semistructured Data and XML / Serge Abiteboul, Peter Buneman, Dan Suciu / 1st Edition / ISBN-13: 978-1558606227 /
ISBN-10: 155860622X
We have ordered 3 printed copies of the coursebook for borrowing - Introduction to Information Retrieval / Christopher Manning, Prabhakar Raghavan, Hinrich Schütze / book and slides available online
supplementary
- Fundamentals of database systems / Ramez Elmasri, Shamkant B. Navathe / 6th edition / ISBN-13: 978-0136086208 / ISBN-10: 0136086209
In Dawsonera as an e-book with one user licence
Computer Science library: one coursebook for borrowing - Advanced Analytics with Spark: Patterns for Learning from Data at Scale / Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills / O'Reilly Media; 1st edition / ISBN-13: 978-1491912768 / ISBN-10: 1491912766
In Safari as an e-book with 3 users licence.
In Ebsco as an e-book with one user licence
Computer Science library: one coursebook for borrowing
Assessment methods
- 3 take-home homeworks, which will include pen-and-paper questions and programming assignments
- in-class final exam
Grace Period for Assignments
Each student has a grace period of 5 late days, to distribute any way they want among the three assignments.Instructors
- Aristides Gionis
- Michael Mathioudakis
Teaching Assistants
Frederick Ayala; frederick.ayala@aalto.fi
Karadahalli Nagesh Shreyas; shreyas.karadahallinagesh@aalto.fi
Phu Pham An; an.pham@aalto.fi
Office hours
by appointment