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

Schedule: Becoming a data-centric company sessions

1:30pm–5:00pm Tuesday, December 6, 2016
Location: 308/309 Level: Intermediate
John Akred (Silicon Valley Data Science), Scott Kurth (Silicon Valley Data Science)
Average rating: ***..
(3.75, 4 ratings)
Big data and data science have great potential for accelerating business, but how do you reconcile the business opportunity with the sea of possible technologies? Data should serve the strategic imperatives of a business—those aspirations that will define an organization’s future vision. Scott Kurth and John Akred explain how to create a modern data strategy that powers data-driven business. Read more.
11:15am–11:55am Wednesday, December 7, 2016
Location: 328/329 Level: Beginner
Mark Madsen (Teradata)
Average rating: **...
(2.00, 1 rating)
In 2007, a computer game company decided to jump ahead of competitors by capturing and using data created during online gaming, but it wasn't prepared to deal with the data management and process challenges stemming from distributed devices creating data. Mark Madsen shares a case study that explores the oversights, failures, and lessons the company learned along its journey. Read more.
12:05pm–12:45pm Wednesday, December 7, 2016
Location: 328/329 Level: Non-technical
Cameron Turner (The Data Guild)
Average rating: ****.
(4.00, 2 ratings)
Huge amounts of data are generated every minute by nearly every company. . .which largely goes unused. Historically, so-called data exhaust has been collected for the purpose of manual analysis in the case of a fault or failure. Cameron Turner explains why companies are increasingly looking to their data exhaust as a valuable asset to influence their revenue and profit through machine learning. Read more.
1:45pm–2:25pm Wednesday, December 7, 2016
Location: 328/329 Level: Non-technical
Devin Deen (enterprise IT), Dnyanesh Prabhu (SKY TV nz)
Average rating: ****.
(4.00, 2 ratings)
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. Read more.
4:15pm–4:55pm Wednesday, December 7, 2016
Location: Summit 1
Jim Scott (NVIDIA)
Average rating: *****
(5.00, 2 ratings)
Application developers have long created complex schemas to handle storing with minor relationships in an RDBMS. This talk will show how to convert an existing (complicated schema) music database to HBase for transactional workloads, plus how to use Drill against HBase for real-time queries. HBase column families will also be discussed. Read more.
4:15pm–4:55pm Wednesday, December 7, 2016
Location: 310/311 Level: Non-technical
Paco Nathan (derwen.ai)
Average rating: **...
(2.00, 1 rating)
O'Reilly recently launched Oriole, a new learning medium for online tutorials that combines Jupyter notebooks, video timelines, and Docker containers run on a Mesos cluster, based the pedagogical theory of computable content. Paco Nathan explores the system architecture, shares project experiences, and considers the impact of notebooks for sharing and learning across a data-centric organization. Read more.
4:15pm–4:55pm Wednesday, December 7, 2016
Location: 328/329 Level: Beginner
Antonio Alvarez (Santander Group)
Average rating: ****.
(4.00, 1 rating)
Santander was one of the last big banks in the UK to start using Hadoop and other big data technologies. However, the maturity of the technology made it possible to create a customer-facing data product in production in less than a year and a fully adopted production analytics platform in less than two. Antonio Alvarez shares what other late entrants can learn from this experience. Read more.
5:05pm–5:45pm Wednesday, December 7, 2016
Location: 328/329 Level: Intermediate
John Akred (Silicon Valley Data Science)
Average rating: *****
(5.00, 1 rating)
The unique properties of data make it difficult to assess its overall value using traditional valuation approaches. John Akred discusses a number of alternative approaches to valuing data within an organization for specific purposes so that you can optimize decisions around its acquisition and management. Read more.
12:05pm–12:45pm Thursday, December 8, 2016
Location: 328/329 Level: Non-technical
John Kreisa (Hortonworks)
Average rating: ***..
(3.50, 2 ratings)
The opportunity to harness data to impact business is ripe, and as a result, every industry, every organization, and every department is going through a huge change, whether they realize it or not. John Kreisa shares use cases from across Asia and Europe of businesses that are successfully leveraging new platform technologies to transform their organizations using data. Read more.
1:45pm–2:25pm Thursday, December 8, 2016
Location: 328/329 Level: Non-technical
Chris Neumann (500 Startups)
Average rating: ****.
(4.75, 4 ratings)
For decades, business intelligence companies have strived to make their products easier to use in the hope that they could finally reach the mythical subject-matter expert—that wondrous individual who would change the course of the company if only she had access to the data she needed. Drawing on his real-world experience, Chris Neumann asks, "What if the subject-matter expert doesn’t exist?" Read more.
5:05pm–5:45pm Thursday, December 8, 2016
Location: 328/329 Level: Non-technical
Franz Aman (Informatica)
Average rating: ****.
(4.33, 3 ratings)
Marketing has become ever more data driven. While there are thousands of marketing applications available, it is challenging to get an end-to-end line of sight and fully understand customers. Franz Aman explains how bringing the data from the various applications and data sources together in a data lake changes everything. Read more.