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

From VistrailsWiki
Jump to navigation Jump to search
Line 20: Line 20:


== Week 2 -- Sept 15: Provenance and Reproducibility ==
== Week 2 -- Sept 15: Provenance and Reproducibility ==
* The class will have a lab component. Please bring your laptops, and have VisTrails installed: http://vistrails.org/index.php/Downloads
* The class will have a lab component. Please bring your laptops.
* Before class, follow the instructions below to install and set up VisTrails
** Download VisTrails from http://vistrails.org/index.php/Downloads


* VisTrails setup:
**
** Download VisTrails 2.1.4 from http://www.vistrails.org/index.php/Downloads and follow the installation instructions. Start the system and then quit.
** Download the following packages:
***http://vgc.poly.edu/~fchirigati/gmaps.zip.
***http://vgc.poly.edu/~fchirigati/tabledata-backport.zip
** After you extract the content of the zip files, place them under $HOME/.vistrails/userpackages
* Github
* During class, you will add the trail of your analysis to github, and submit the link to your public github repo using this form: https://docs.google.com/forms/d/17OScN8Ea-El20AC4mHIb32S3e62mAbGEiU-BET0PyX8/viewform?usp=send_form


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

Revision as of 18:39, 13 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

  • The class will have a lab component. Please bring your laptops.
  • Before class, follow the instructions below to install and set up VisTrails

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