Presented By O'Reilly and Cloudera
December 5-6, 2016: Training
December 6–8, 2016: Tutorials & Conference
Singapore

Smart cities conference sessions

1:45pm–2:25pm Thursday, 12/08/2016
One challenge when dealing with manufacturing sensor data analysis is to formulate an efficient model of the underlying physical system. Rajesh Sampathkumar shares his experience working with sensor data at scale to model a real-world manufacturing subsystem with simple techniques, such as moving average analysis, and advanced ones, like VAR, applied to the problem of predictive maintenance.
1:45pm–2:25pm Wednesday, 12/07/2016
Embedding operational analytics with the IoT enables organizations to act on insights in real time. Devin Deen and Dnyanesh Prabhu walk you through examples from Sky TV and NZ Bus—two businesses that iteratively developed their analytic capabilities integrating the IoT on Hadoop, allowing people and process changes to keep pace with technical enablement.
11:15am–11:55am Thursday, 12/08/2016
The interconnected world presents unprecedented opportunities to gain new insights on behavior, both human and nonhuman alike. Likewise, it also poses unprecedented challenges on how organizations can act on these moments of opportunities in time. Michael O'Connell and San Zaw share real-world case studies demonstrating how real-time analytics solves these challenges.
2:35pm–3:15pm Thursday, 12/08/2016
Jennifer Marsman, Ranveer Chandra, and Wee Hyong Tok explore the various drone technologies that are currently available and explain how to acquire and analyze real-time signals from drones to design intelligent applications.
5:05pm–5:45pm Thursday, 12/08/2016
Data ethics covers more than just privacy. In a connected world where most people rely on data-driven services, opting out and locking data away is hardly an option. More important than keeping data private is ensuring fairness and preventing abuse. Joerg Blumtritt and Heather Dewey-Hagborg show how to deal with data in an ethical way that has sound economic value.
11:15am–11:55am Thursday, 12/08/2016
Translating streaming, real-time telecommunications data into actionable analytics products remains challenging. Boon Siew Seah explores SmartHub’s past successes and failures building telco analytics products for its customers and shares the big data technologies behind its two API-based telco analytics products: Grid360 (geolocation analytics) and C360 (consumer insights).
5:05pm–5:45pm Wednesday, 12/07/2016
Creating big data solutions that can process data at terabyte scale and produce spatial-temporal real-time insights at speed demands a well-thought-through system architecture. Chandras Sekhar Saripaka details the production architecture at DataSpark that works through terabytes of spatial-temporal telco data each day in PaaS mode and showcases how DataSpark operates in SaaS mode.
11:00am–11:30am Tuesday, 12/06/2016
In early 2016, a team set out to score the usability of government open data across 5 countries. What was to be a small-scale project giving a data-driven picture of the supply side of open data grew into a lengthy, all-consuming quest to decipher the depths of government CKAN repositories. Audrey Lobo-Pulo shares the team's findings and explores the future possibilities of open data.
5:05pm–5:45pm Wednesday, 12/07/2016
Takayuki Nishikawa and Ei Yamaguhi explain how Panasonic developed an integrated data analytics platform to analyze the increasing number of home appliances logs from its IoT products, achieving scalability for millions of households and a 10x improvement in processing time with Hadoop and Hive, in the process gaining more reliable knowledge about users’ lifestyles with Spark MLlib.
2:35pm–3:15pm Wednesday, 12/07/2016
Combining the power of the IoT and big data analytics opens the doors to a wide range of opportunities for organizations to solve new challenges that create an impact on the world that we live in. Frank Saeuberlich and Karthik Thirumalai explain why data management, data integration, and multigenre analytics are foundational to driving business value from IoT initiatives.
1:45pm–2:25pm Wednesday, 12/07/2016
Shao Wei Ying explains how mobility intelligence derived from telco big data informs us about the state of our urban infrastructure, economic activities, and public safety.
12:05pm–12:45pm Thursday, 12/08/2016
Modern telecommunications are alphabet soups that produce massive amounts of diagnostic data. Ted Dunning offers an overview of a real-time, low-fidelity simulation of the edge protocols of such a system to help illustrate how modern big data tools can be used for telecom analytics. Ted demos the system and shows how several tools can produce useful analytical results and system understanding.
2:35pm–3:15pm Thursday, 12/08/2016
Do you want to persuade finance to fund a Hadoop cluster? Educate designers & architects to use Hadoop in their solutions? Get a data team to run Hadoop as a shared service? Democratize your data? Stop by and find out how Phillip did it, he’s got some great ideas for you.
10:15am–10:35am Thursday, 12/08/2016
M. C. Srivas covers the technologies underpinning the big data architecture at Uber and explores some of the real-time problems Uber needs to solve to make ride sharing as smooth and ubiquitous as running water, explaining how they are related to real-time big data analytics.