COLORADO Event Schedule
April
22
Colorado
 
  Big Data Science Fair by Precog
Event Details

Sponsored by:
        
Can you open peoples eyes with data?
Whether you are mapping the ocean floor, looking for the cure for a disease, or trying to recommend to products to . . .customers, big data is changing how we solve problems in the world!
Come and see dozens of big data visualizations and projects set up science fair style at the new Fuse coworking space. There will be a mix of CU students and tech companies showing how they are using data to uncover the answers to questions and solve problems.
Walk around and vote on your mobile phone via text message to nominate presentations for awards like:
- Impactful Insight
- Creative Champion
- Judges Choice

 
Materials for trophies donated by Denver Metro Metal Recycling
Additonal Prizes Sponsored by
 
Presenters
15 CU Graduate Students from Professor Tom Yeh’s Big Data class will be presenting their semester projects.
Tech companies including Precog, Gnip, Trueffect, Tagwhat, Geosales, RoseBT and more!
 
Details

Free Pizza, Beer, and Drinks!

Bring your cell phone so that you can text to vote and nominate your favorite presentations for prizes

 
Interested in presenting at the Big Data Science Fair?
Enter to be a presenter at this link: https://docs.google.com/forms/d/148ygBOBl90edhtwhEDhPy-9hPLBsSs8-OY_poNWSJWQ/viewform
Do you know someone who would make for a good presenter? Please share the link above!

Sponsorship
If your company is interested in sponsoring the Big Data Science Fair please contact Daniel Vitiello – Daniel@actnow.io
Precog | Gnip | Quickleft | Denver Metro Recycling

 
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Timing: 5:00pm – 7:00pm
Theme: Cross Sector

Organised by Daniel Vitiello
Daniel@actnow.io

  Level: Basic
Format: Multi-Format

April
23
Colorado
 
  Big Data & Coffee at TechStars
Come and enjoy free coffee and bagels April 23 from 8:00 AM – 10:00 AM at Techstars as part of Big Data Week/Colora http://bigdataweek.com/colorado/

Get your day started by listening to an exciting . . .panel of big movers and business owners involved in Big Data in the Denver/Boulder Metro region as well as from San Francisco.
These Big Data leaders will not only share what they are doing individually within their own businesses and organizations to leverage “lessons learned” from past IT business cycles but also speak to how Big Data can be used as a catalyst to build a strong, profitable, and sustainable Information Technology and R&D ecosystem here in the Rockies that contributes globally.

PANEL MEMBERS: 
John De Goes, CEO & CTO – http://www.precog.com/
Jim Franklin, CEO – http://www.sendgrid.com/
Narenedra Patil,SVP Marketing – http://www.ngdata.com/
Ken Anderson, Ph.D., Associate Chair of Computer Science  - http://www.cs.colorado.edu/~kena/
Christian Macy, Owner and Entrepreneur – http://boulderfuse.com/

ADDRESS:  Techstars Suite 202, 1050 Walnut St. Boulder, CO 80302
 
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Timing: 8:00am – 10:00am
Theme: Data & Communications

Organised by Precog
g_gottlich@yahoo.com

  Level: Intermediate
Format: Breakfast meeting

April
23
Colorado
 
  Spark, Shark and Mesos Data Analytics Stack on a Hadoop Cluster
Spark, Shark and Mesos Data Analytics Stack on a Hadoop Cluster
This presentation will introduce Spark, Shark and Mesos Data Analytics Stack on a Hadoop Cluster.
The Berkeley Data Analytics Stack (BDA . . .S) is an open source, next-generation data analytics stack under development at the UC Berkeley AMPLab whose current components include Spark, Shark and Mesos.
One flaw of Hadoop MapReduce is high latency. Considering the growing volume, variety and velocity of data, organizations and data scientists require faster analytical platforms. Put simply, speed kills and Spark gains speed through caching and optimizing the master/node communications.
Spark is an open source cluster computing system that makes data analytics fast. To run programs faster, Spark provides primitives for in-memory cluster computing: your job can load data into memory and query it repeatedly much quicker than with disk-based systems like Hadoop MapReduce.
Spark is a high-speed cluster computing system compatible with Hadoop that can outperform it by up to 100 times considering its ability to perform computations in memory. It is a computation engine built on top of the Hadoop Distributed File System (HDFS) that efficiently support iterative processing (e.g., ML algorithms), and interactive queries. Spark provides an easy-to-program interface that is available in Java, Python, and Scala. Spark Streaming is a component of Spark that provides highly scalable, fault-tolerant streaming processing. With this functionality, Spark provides integrated support for all major computation models: batch, interactive, and streaming.
Shark is a large-scale data warehouse system that runs on top of Spark and is backward-compatible with Apache Hive, allowing users to run unmodified Hive queries on existing Hive workhouses. Shark is able to run Hive queries 100 times faster when the data fits in memory and up to 5-10 times faster when the data is stored on disk. Shark is a port of Apache Hive onto Spark that is compatible with existing Hive warehouses and queries. Shark can answer HiveQL queries up to 100 times faster than Hive without modification to the data and queries, and is also open source as part of BDAS.
The Shark data analysis warehouse system:
- builds on Spark (MapReduce deterministic, idempotent tasks)
- scales out and is fault-tolerant
- supports low-latency, interactive queries through in-memory computation
- supports both SQL and complex analytics such as machine learning
- is compatible with Apache Hive (storage, serdes, UDFs, types, metadata)
By using Spark as the execution engine and employing novel and traditional database techniques, Shark bridges the gap between MapReduce and MPP databases.
Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications such as Hadoop, MPI, Hypertable, and Spark. As a result, Mesos allows users to easily build complex pipelines involving algorithms implemented in various frameworks.

Highlights

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Timing: 6:00pm – 8:30pm
Theme: Cross Sector

Organised by Data Science & Business Analytics
m@rosebt.com

  Level: Advanced
Format: Meetup

April
24
Colorado
 
  Machine Learning & Behavioral Analytics
Want to know how to make your data smarter? Do you want to use your existing data to make predictions, classify data or provide recommendations? Do you want understand more about what your users are d . . .oing?
You’re invited to the Machine Learning & Behavioral Analytics meetup on Wednesday, April 24th in Denver at the SendGrid offices. Please RSVP on the meetup page to save a spot.
You’ll first hear from Will Stanton on an introduction to machine learning to understand what machine learning is and how you can apply it to your data. Next you’ll hear from Ben Johnson on behavioral analytics and how you can use the open source Sky database for extremely fast processing of clickstream and log data.
Join us for drinks, pizza, an interactive dialogue, and to learn more about how to get the most out of your data.
Parking: Metered street parking and paid lots are available nearby the SendGrid offices. Map
Agenda
6:00 – 6:30 – Socialize over food and drink
6:30 – 6:45 – Announcements, Upcoming Events
6:45 – 7:30 – Machine Learning – Will Stanton
7:30 – 8:15 – Behavioral Analytics using Sky – Ben Johnson
8:15 – ??? – Continued socializing
About the presenters
Will Stanton
Will is a PhD student at CU Boulder studying mathematics. His thesis is on Random Matrix Theory, a field with surprising connections to big data analytics. He has spoken at several universities, including CU Boulder and the University of Wisconsin – Madison. After completing his PhD in May, Will is going to start an internship at Return Path, working with their analytics team on interesting problems in the world of email data.
Ben Johnson
Ben has worked in a variety of data-related roles from being an Oracle DBA to designing front-end data visualizations. For the last year he has worked on an open source NoSQL database called Sky that is specifically optimized for working with large behavioral datasets such as clickstream and log data. He is the founder of a data science consulting company called Skyland Labs in Denver.
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Timing: 6:00pm – 8:30pm
Theme: Data & Communications

Organised by Boulder Denver Big Data
Daniel@actnowapp.com

  Level: Intermediate
Format: Presentation

CITY ESSENTIALS – COLORADO


Official Hashtag #bdw13
City contacts
Daniel Vitiello
Daniel@actnow.io
 
 

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