Workshop
Sunday, April 3 2016
Full day: 9:00am - 4:30pm
Room: Salon 3 & 4
Big Data: Proven Methods You Need to Extract Big Value
Intended Audience: Managers, decision makers, practitioners, and professionals interested in a broad overview and introduction
Knowledge Level: All levels
Attendees will receive an electronic copy of the course notes and materials
Workshop Description
"Big Data" is everywhere. The topic is impacting every industry and institution. Big excitement about big data comes from the intersection of dramatic increases in computing power and data storage with growing streams of data coming from almost every person and process on Earth. The pressing question is, how do we best make value of all this data - what should we do with it?
Working with big data effectively depends on understanding the sources of data and the issues in storing and analyzing it:
- Where does big data come from?
- How do you manage, store, and compute on big data?
- What qualifies as "big"?
This one day workshop reviews major big data success stories that have transformed businesses and created new markets.
Dr. Smith will cover these revealing stories in order to illustrate the key concepts, tools, and value-proven applications driving the big data revolution.
"Big data" is a open buzzword - it could be defined as any amount of data you can't afford to handle - but the big, newfound value achieved by computing at scale is no fad.
What you will learn:
- Where does big data come from: Common sources of big data.
- What makes data big: Velocity, Variety, and Volume!
- How can we leverage it: Open tools and platforms for storing and analyzing big data.
- The new paradigm: Today's shift from hypothesis testing to a broad exploration for correlations is a revolutionary change in the way data is explored.
- Best practices for analyzing big data: Key methods in data science, predictive analytics, and text analytics to analytically learn from data.
- Social Data: Finding key connections in webs of people and events.
- Applications of big data insights to business.
- Future directions in big data: bigger, bolder, and better.
Schedule
- Workshop starts at 9:00am
- Morning Coffee Break at 10:30am - 11:00am
- Lunch provided at 12:30 - 1:15pm
- Afternoon Coffee Break at 2:30pm - 3:00pm
- End of the Workshop: 4:30pm
Attendees receive a copy of the course materials book at the beginning of the workshop.
Instructor
Dr. Marc A. Smith, Chief Social Scientist, Connected Action Consulting Group
[email protected]
http://www.connectedaction.net
http://delicious.com/marc_smith/
http://nodexl.codeplex.com
http://twitter.com/marc_smith
http://www.smrfoundation.org/
Marc Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group and lives and works in Silicon Valley, California. Smith co-founded the Social Media Research Foundation (http://www.smrfoundation.org/), a non-profit devoted to open tools, data, and scholarship related to social media research.
Smith is the co-editor with Peter Kollock of Communities in Cyberspace (Routledge), a collection of essays exploring the ways identity; interaction and social order develop in online groups. Along with Derek Hansen and Ben Shneiderman, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interactions.
Smith's research focuses on computer-mediated collective action: the ways group dynamics change when they take place in and through social cyberspaces. Many "groups" in cyberspace produce public goods and organize themselves in the form of a commons (for related papers see: http://www.connectedaction.net/marc-smith/). Smith's goal is to visualize these social cyberspaces, mapping and measuring their structure, dynamics and life cycles. While at Microsoft Research, he founded the Community Technologies Group and led the development of the "Netscan" web application and data mining engine that allowed researchers studying Usenet newsgroups and related repositories of threaded conversations to get reports on the rates of posting, posters, crossposting, thread length and frequency distributions of activity. He contributes to the open and free NodeXL project (http://www.codeplex.com/nodexl) that adds social network analysis features to the familiar Excel spreadsheet. NodeXL enables social network analysis of email, Twitter, Flickr, WWW, Facebook and other network data sets.
The Connected Action consulting group (http://www.connectedaction.net) applies social science methods in general and social network analysis techniques in particular to enterprise and internet social media usage. SNA analysis of data from message boards, blogs, wikis, friend networks, and shared file systems can reveal insights into organizations and processes. Community managers can gain actionable insights into the volumes of community content created in their social media repositories. Mobile social software applications can visualize patterns of association that are otherwise invisible.
Smith received a B.S. in International Area Studies from Drexel University in Philadelphia in 1988, an M.Phil. in social theory from Cambridge University in 1990, and a Ph.D. in Sociology from UCLA in 2001. He is an adjunct lecturer at the College of Information Studies at the University of Maryland. Smith is also a Distinguished Visiting Scholar at the Media-X Program at Stanford University.
