conference

Strata + Hadoop World 2016 - Singapore

by O'Reilly Media, Inc.

December 2016

62h 47m

English

Closed Captioning available in German, English, Spanish, French, Japanese, Korean, Portuguese (Portugal, Brazil), Chinese (Simplified), Chinese (Traditional)

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Course outline

A smarter ecosystem through big data analytics - Wei Keong Ng (Fusionex)
12m 38s
Big data, big value for smart banking at DBS - Mike Olson (Cloudera) and David Gledhill (DBS Bank)
15m 15s
Disruption in insurance: Seven predictions - Zia Zaman (MetLife)
21m 9s
Image intelligence: Making visual content predictive - Susan Etlinger (Altimeter Group)
15m 47s
Information at the speed of thought - Prakash Nanduri (Paxata)
3m 45s
Real-time intelligence gives Uber the edge - M. C. Srivas (Uber)
17m 53s
Taking personalization personally - Sara Watson (Tow Center for Digital Journalism)
24m 0s
The ACID revolution - Vijay Narayanan (Microsoft)
12m 11s
The new dynamics of Big Data - Amr Awadallah (Cloudera, Inc.)
8m 51s
What if data had personality? - Julie Rodriguez (Sapient Global Markets)
11m 34s
Developing a modern enterprise data strategy - John Akred (Silicon Valley Data Science) and Scott Kurth (Silicon Valley Data Science) - Part 1
44m 35s
Developing a modern enterprise data strategy - John Akred (Silicon Valley Data Science) and Scott Kurth (Silicon Valley Data Science) - Part 2
45m 50s
Developing a modern enterprise data strategy - John Akred (Silicon Valley Data Science) and Scott Kurt (Silicon Valley Data Science) - Part 3
45m 8s
Developing a modern enterprise data strategy - John Akred (Silicon Valley Data Science) and Scott Kurt (Silicon Valley Data Science) - Part 4
47m 11s
Dealing with device data - Mark Madsen (Third Nature)
42m 9s
Act on insight with the IoT - Devin Deen (enterprise IT) and Dnyanesh Prabhu (SKY TV nz)
39m 59s
Evolving from RDBMS to NoSQL + SQL - Jim Scott (MapR Technologies, Inc.)
32m 8s
First mover or fast follower? Santander UK's big data journey - Antonio Alvarez (Santander Group)
43m 45s
Computable content: Notebooks, containers, and data-centric organizational learning - Paco Nathan (O'Reilly Media)
39m 8s
What's your data worth? - John Akred (Silicon Valley Data Science)
44m 13s
Case studies of business transformation through big data - John Kreisa (Hortonworks)
40m 9s
The fallacy of the subject-matter expert - Chris Neumann (The Engineer & The Designer)
27m 0s
How to use a marketing data lake for data-driven marketing - Franz Aman (Informatica)
44m 38s
Experience in adopting deep learning into existing software development practices - Verdi March (Deep Labs)
36m 50s
Context-aware recommendations using reinforcement learning in the item-similarity space - Arun Veettil (Starbucks)
40m 23s
Applications of natural language understanding: Tools and technologies - Alyona Medelyan (Thematic)
31m 5s
High-efficiency systems for distributed AI and machine learning at scale - Qirong Ho (Petuum, Inc.)
37m 32s
Machine learning in practice with Spark MLlib: An intelligent data analyzer - Flavio Clesio (Movile) and Eiti Kimura (Movile)
40m 7s
Deep reinforcement learning on Spark - Adam Gibson (Skymind)
44m 28s
Cloud AI innovations - Graham Williams (Microsoft), Hong Ooi (Microsoft), and Ted Minkinow (Fullerton Health)
43m 36s
Transfer learning and fine-tuning deep neural network models across different domains - Anusua Trivedi (Microsoft)
42m 4s
Fast deep learning at your fingertips - Nir Lotan (Intel)
32m 22s
How Lazada ranks products to improve customer experience and increase conversion - Eugene Yan (Lazada)
45m 9s
Creating real-time, data-centric applications with Impala and Kudu - Marcel Kornacker (Cloudera) and Todd Lipcon (Cloudera)
52m 19s
Web-scale machine learning on Apache Spark - Jason (Jinquan) Dai (Intel)
32m 21s
Machine learning: The power of ensembles - Bargava Subramanian (Cisco Systems) and Amit Kapoor (narrativeVIZ Consulting)
41m 14s
Understanding the voice of members via text mining: How Linkedin built a text analytics engine at scale - Chi-Yi Kuan (LinkedIn), Weidong Zhang (LinkedIn), and Yongzheng Zhang (LinkedIn)
42m 54s
A survey of time series analysis techniques for sensor data - Rajesh Sampathkumar (The Data Team)
41m 46s
Deep learning at scale - Mateusz Dymczyk (H2O.ai)
41m 32s
Concepts before machinery: Harnessing the power of domain expertise for machine-learning-based solutions - Ofer Ron (LivePerson)
35m 29s
Deep learning for natural language processing - Bargava Subramanian (Cisco Systems) and Amit Kapoor (narrativeVIZ Consulting)
44m 18s
Using big data technology to solve data connectivity in a disconnected world - Imron Zuhri (Dattabot)
38m 9s
Encoding new data visualizations - Piotr Kaczmarek (Sapient Global Markets) and Julie Rodriguez (Sapient Global Markets)
39m 13s
Hadoop as a service at BT: How to build a successful enterprise data hub - Phillip Radley (BT)
48m 15s
Crawling and tracking millions of ecommerce products at scale - Qiaoliang Xiang (Shopback)
45m 25s
How to apply big data solutions in the semiconductor industry - Rebecca Tien Yu Lin (is-land Systems Inc.)
38m 0s
Learn stream processing with Apache Beam - Tyler Akidau (Google), Slava Chernyak (Google), Dan Halperin (Google), Sandeep Deshmukh (DataTorrent), and Aljoscha Krettek (Data Artisans) - Part 1
56m 13s
Learn stream processing with Apache Beam - Tyler Akidau (Google), Slava Chernyak (Google), Dan Halperin (Google), Sandeep Deshmukh (DataTorrent), and Aljoscha Krettek (Data Artisans) - Part 2
57m 13s
IoT and Spark MLlib applications for improving products, services, and manufacturing technologies - Masaru Dobashi (NTT DATA Corporation) and Yoshitaka Suzuki (IHI Corporation)
42m 19s
Twitter's real-time stack: Processing billions of events with Heron and DistributedLog - Maosong Fu (Twitter)
40m 11s
Architecting a hybrid cloud application using a global publish-subscribe streaming message system - Mathieu Dumoulin (MapR Technologies)
37m 19s
Watermarks and triggers: Time and progress in Apache Beam (incubating) and beyond - Slava Chernyak (Google)
36m 21s
Making sense of the sensors: Connecting the IoT and analytics - Frank Saeuberlich (Teradata) and Karthik Bharadwaj Thirumalai (Teradata)
39m 27s
Industrial big data and sensor time series data: Different but not difficult—Part II - Gopal GopalKrishnan (OSIsoft, LLC.) and Chris Soyza (BEARS)
38m 4s
A simplified enterprise architecture for real-time stream processing - Mathieu Dumoulin (MapR Technologies)
42m 33s
Robust stream processing with Apache Flink - Aljoscha Krettek (data Artisans)
42m 44s
Just enough Scala for Spark - Dean Wampler (Lightbend) - Part 1
33m 28s
Just enough Scala for Spark - Dean Wampler (Lightbend) - Part 2
52m 24s
Just enough Scala for Spark - Dean Wampler (Lightbend) - Part 3
36m 18s
Just enough Scala for Spark - Dean Wampler (Lightbend) - Part 4
37m 51s
Building and tuning machine-learning apps using Spark ML and GraphX Libraries - Jayant Shekhar (Sparkflows Inc.) and Vartika Singh (Cloudera) - Part 1
50m 29s
Building and tuning machine-learning apps using Spark ML and GraphX Libraries - Jayant Shekhar (Sparkflows Inc.) and Vartika Singh (Cloudera) - Part 2
43m 5s
Building and tuning machine-learning apps using Spark ML and GraphX Libraries - Jayant Shekhar (Sparkflows Inc.) and Vartika Singh (Cloudera) - Part 3
49m 51s
Building and tuning machine-learning apps using Spark ML and GraphX Libraries - Jayant Shekhar (Sparkflows Inc.) and Vartika Singh (Cloudera) - Part 4
37m 26s
How Alluxio (formerly Tachyon) brings a 300x performance improvement to Qunar’s streaming processing - Xueyan Li (Qunar)
29m 59s
The business case for Spark, Kafka, and friends - John Akred (Silicon Valley Data Science)
42m 19s
Scala and the JVM as a big data platform: Lessons from Apache Spark - Dean Wampler (Lightbend)
44m 7s
Alluxio (formerly Tachyon): An open source memory-speed virtual distributed storage system - Jiri Simsa (Alluxio)
40m 43s
From telco data to spatial-temporal intelligence APIs: Architecting through microservices - Chandras Sekhar Saripaka (DataSpark)
45m 32s
Spark Structured Streaming for machine learning - Holden Karau (IBM) and Seth Hendrickson (IBM)
39m 49s
How Mediacorp has leveraged Apache Spark and Microsoft Cloud to analyze patterns of user behavior for actionable insights - Andrea Gagliardi La Gala (Microsoft)
45m 40s
Apache Spark: Enterprise security for production deployments - Vinay Shukla (Hortonworks)
41m 16s
Writing reusable visualization software with D3.js: Part I - Michael Freeman (University of Washington)
50m 0s
Writing reusable visualization software with D3.js: Part II - Michael Freeman (University of Washington)
36m 55s
Data distillation: Applying design principles to reporting, KPI, and dashboards - Patrick Nord (Archetype SC)
35m 56s
The feels: How to design data visualizations that evoke an emotion from your users - Vivian Peng (Doctors Without Borders)
34m 53s
Algorithmic art and data creativity - Joerg Blumtritt (Datarella) and Heather Dewey-Hagborg (School of the Art Institute of Chicago)
41m 22s
Apache Beam: A unified model for batch and streaming data processing - Dan Halperin (Google)
42m 24s
Support digital applications with a resilient, highly available, and NRT Hadoop backend - Nicolette Bullivant (Isban UK, Santander Group) and Jorge Pablo Fernandez (Isban UK, Santander Group)
38m 29s
BI and SQL analytics with Hadoop in the cloud - Alex Gutow (Cloudera) and Henry Robinson (Cloudera)
42m 40s
Organizing the data lake - Mark Madsen (Third Nature)
44m 50s
Securing big data on YARN, Hive, and Spark clusters - Nitin Khandelwal (Qubole) and Abhishek Modi (Qubole)
32m 38s
Authorization in the cloud: Enforcing access control across compute engines - Hao Hao (Cloudera) and Alex Leblang (Cloudera)
36m 3s
Next-generation data governance - Clara Fletcher (Accenture)
26m 33s

Content preview from Strata + Hadoop World 2016 - Singapore

Evolving beyond the data lake - Jim Scott (MapR Technologies, Inc.)

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Publisher Resources

ISBN: 9781491958551Errata Page

Strata + Hadoop World 2016 - Singapore

by O'Reilly Media, Inc.

Keynotes

Becoming a data-centric company

Chat, machine learning, & AI

Data science & advanced analytics

Hadoop use cases

IoT & intelligent real-time applications

Spark & beyond

Design, visualization, & VR

Production-ready Hadoop

Security & governance

Smart cities & urban automation

Sponsored

Data innovations

Law, ethics, open data

Data Case Studies

Content preview from Strata + Hadoop World 2016 - Singapore

Evolving beyond the data lake - Jim Scott (MapR Technologies, Inc.)

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.

You might also like

Strata + Hadoop World Singapore 2015: Video Compilation

Strata Data Conference 2017 - Singapore

Strata + Hadoop World 2016 - London, United Kingdom: Video Compilation

The Java Sessions: The Best of OSCON 2011

Publisher Resources

Keynotes

Becoming a data-centric company

Chat, machine learning, & AI

Data science & advanced analytics

Hadoop use cases

IoT & intelligent real-time applications

Spark & beyond

Design, visualization, & VR

Production-ready Hadoop

Security & governance

Smart cities & urban automation

Sponsored

Data innovations

Law, ethics, open data

Data Case Studies

Content preview from Strata + Hadoop World 2016 - Singapore

Evolving beyond the data lake - Jim Scott (MapR Technologies, Inc.)

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,and much more.

You might also like

Strata + Hadoop World Singapore 2015: Video Compilation

Strata Data Conference 2017 - Singapore

Strata + Hadoop World 2016 - London, United Kingdom: Video Compilation

The Java Sessions: The Best of OSCON 2011

Publisher Resources

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.