Difference between revisions of "Course: Massive Data Analysis 2014"

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* Course survey: https://docs.google.com/spreadsheet/embeddedform?formkey=dFpwTjROVzhLUWY2NVNXb0xvNTVLMnc6MA
* Course survey: https://docs.google.com/spreadsheet/embeddedform?formkey=dFpwTjROVzhLUWY2NVNXb0xvNTVLMnc6MA


== Week 2 -- Sept 15: Introduction to Databases ==
== Week 2 -- Sept 15: Provenance and Reproducibility ==
* Lecture notes:  http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/intro-to-db.pdf
* The class will have a lab component. Please bring your laptops, and have VisTrails installed: http://vistrails.org/index.php/Downloads
* Other useful reading:  
** [http://philip.greenspun.com/sql/introduction.html Greenspun's SQL for Web Nerds Intro]
** [http://philip.greenspun.com/sql/data-modeling.html SQL/Nerds Modeling (parts)]




== Week 3 -- Sept 22: Overview: Relational Model and SQL ==
== Week 3 -- Sept 22: Introduction to Databases; Relational Model and SQL ==
* Lecture notes:   
* Lecture notes:   
**http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/intro-to-db.pdf
** http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/relational-algebra.pdf
** http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/relational-algebra.pdf
** http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/sql-intro.pdf
** http://vgc.poly.edu/~juliana/courses/MassiveDataAnalysis2014/Lectures/sql-intro.pdf

Revision as of 15:41, 8 September 2014

CS-GY 6333 Massive Data Analysis: Tentative Schedule -- subject to change

  • Lecture: Mondays, 1:00pm-3:25pm at 2MTC, room 9.011.

News

  • Welcome!

Background (4 weeks)

Week 1 -- Sept 8: Course Overview; the evolution of Data Management

Week 2 -- Sept 15: Provenance and Reproducibility


Week 3 -- Sept 22: Introduction to Databases; Relational Model and SQL


Week 4 -- Sept 29: Overview: Advanced SQL and Query Optimization


Big Data Foundations and Infrastructure (3 weeks)

Week 5 -- Oct 6: Cloud computing, Map Reduce and Hadoop

  • Required reading:
    • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
    • Mining of Massive Datasets (2nd Edition), Chapter 2 - 2.1 and 2.2 (Large-Scale File Systems and Map-Reduce).


Week 6 -- Oct 13: Fall Break

Week 7 -- Oct 20: Algorithm Design for MapReduce

  • Required reading:
    • Data-Intensive Text Processing with MapReduce, Chapters 1 and 2
    • Mining of Massive Datasets (2nd Edition), Chapter 2.


Week 8 -- Oct 27: Parallel Databases vs MapReduce, Query Processing on Mapreduce and High-level Languages



Big Data Algorithms and Techniques (3 weeks)

Week 9 -- Nov 3: Association Rules


Week 10 -- Nov 10: Finding similar items


Week 11 -- Nov 17: Graph Analysis


Week 12 -- Nov 25: Large-Scale Visualization -- Invited lecture by Dr. Lauro Lins (AT&T Research)

  • Reading:

The Value of Visualization, Jarke Van Wijk http://www.win.tue.nl/~vanwijk/vov.pdf

Tamara Munzner's Book draft 2 available online http://www.cs.ubc.ca/~tmm/courses/533/book/

Nanocubes Paper http://nanocubes.net http://nanocubes.net/assets/pdf/nanocubes_paper_preprint.pdf


Week 13 -- Dec 1:

Week 14 -- Dec 8: Project Presentations

Week 15 -- Dec 15: Project Presentations

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