Methodologies to Improve Big Bata Projects
As data continues to be produced in massive amounts, with increasing volume, velocity and variety, Big Data projects are growing in frequency and importance. However, the growth in the use of Big Data has outstripped the knowledge of how to support teams that need to do big data projects.
In fact, there has been very little written about methodologies, processes and frameworks that could enable teams to more effectively and efficiently “do” big data projects. The situation is much like the early days of software development: software was being developed but organizations had little ability to predict whether a project would be successful, on time or on budget and projects were overly reliant on the heroic efforts of particular individuals.
The first annual workshop on methodologies and tools to improve big data projects will be held in conjunction with IEEE Big Data 2015, to be held in Santa Clara, CA, USA on Oct 29 – Nov 1, 2015.
In this workshop, we will explore methodologies, processes, frameworks and tools to support data teams - that have been or need to be developed to help support Big Data projects. Specifically, this workshop will focus on how we can best support effective communication, collaboration and the overall execution by a Big Data team.
The workshop will provide a venue to explore new ideas in possible methodologies as well case studies that describe examples of what has, or has not, worked within different Big Data teams. To enable a cross pollination of ideas, the workshop welcomes both academic researchers and industry experts to attend.
- Jeffrey Saltz, Syracuse University (Chair)
- Bintong Chen, University of Delaware
- Kevin Crowston, Syracuse University
- Alexandros Labrinidis, University of Pittsburgh
- Jason Dedrick, Syracuse University
- Rakshit Kapoor, Hartford Insurance
- Tayo Ibikunle, JP Morgan Chase
Contact / Questions
Please email any questions to jsaltz[at]syr.edu
Please join our group