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

Data Case Studies

9:00am-12:30pm
Location: 308/309

From banking to biotech, retail to government, nonprofit to energy, every business sector is changing in the face of abundant data. Driven by competitive pressures and rising consumer expectations, firms are getting better at defining business problems and applying data solutions. The road to a data-driven business is paved with hard-won lessons, painful mistakes, and clever insights. We’re introducing a new Tutorial Day track packed with case studies, where you can hear from practitioners across a wide range of industries. We call this track Data Case Studies. In a series of 12 half-hour talks aimed at a business audience, you’ll hear from household brands and global companies as they explain the challenges they wanted to tackle, the approaches they took, and the benefits—and drawbacks—of their solutions. If you want practical insights about applied data, look no further.

Tuesday, 12/06/2016

9:05am

9:05am–9:30am Tuesday, 12/06/2016
DCS
Location: 308/309 Level: Non-technical
Lyudmila Lugovskaya (Lloyds Bank), Stuart Coleman (Lloyds Banking Group)
Average rating: ****.
(4.60, 5 ratings)
Lyudmila Lugovskaya and Stuart Coleman discuss some of the many challenges that organizations face on their journey to become data-centric and share lessons learned from their experience doing and promoting data science within organizations of different type and size while dealing with restrictions imposed by traditional governance structures and policies. Read more.

9:30am

9:30am–10:00am Tuesday, 12/06/2016
DCS
Location: 308/309 Level: Intermediate
Sarang Anajwala (Autodesk)
Average rating: ***..
(3.00, 4 ratings)
Sarang Anajwala discusses Autodesk’s next-generation data platform and its transition from an application for usage analytics to a platform for data analytics that provides capabilities like self-service ETLs, data exploration, multitenant data apps, and data products. This versatile platform supports use cases right from dashboards to data science, helping the move into a data-centric future. Read more.

10:00am

10:00am–10:30am Tuesday, 12/06/2016
DCS
Location: 308/309 Level: Non-technical
Yantisa Akhadi (Humanitarian OpenStreetMap Team)
Average rating: *****
(5.00, 2 ratings)
The use of maps in disaster response is evidently important. Yantisa Akhadi explores how to use OpenStreetMap (OSM), the biggest crowdsourced mapping platform, for safer urban environments, drawing on case studies from several major cities in Indonesia where citizen and government mapping has played a major role in improving resilience. Read more.

11:00am

11:00am–11:30am Tuesday, 12/06/2016
DCS
Location: 308/309 Level: Non-technical
Audrey Lobo-Pulo (Phoensight)
Average rating: ***..
(3.00, 4 ratings)
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. Read more.

11:30am

11:30am–12:00pm Tuesday, 12/06/2016
DCS
Location: 308/309 Level: Intermediate
Amit Rustagi (SanDisk, Western Digital Brand), jingwen ouyang (SanDisk, Western Digital Brand)
Average rating: ***..
(3.50, 4 ratings)
In semiconductor manufacturing, creating a high-yield process where sufficient portions of chips pass acceptance testing is extremely difficult to achieve. Data is collected and analyzed at every stage to improve yield and productivity. Amit Rustagi and Jingwen Ouyang share a Hadoop-based solution that reveals the true value and benefits of manufacturing data generated about every chip. Read more.

12:00pm

12:00pm–12:30pm Tuesday, 12/06/2016
DCS
Location: 308/309 Level: Intermediate
Tags: iot, sports
Asit Parija (MapR Technologies)
Average rating: ****.
(4.00, 1 rating)
Modern cars produce data. Lots of data. And Formula 1 cars produce more than their fair share. Ted Dunning presents a demo of how data streaming can be applied to the analytics problems posed by modern motorsports. Although he won't be bringing Formula 1 cars to the talk, Ted demonstrates a physics-based simulator to analyze realistic data from simulated cars. Read more.