Strata + Hadoop World Singapore 2015: Video Compilation

Table of contents

1. Keynotes
   1. How To Stop Worrying and Learn to Love Qualitative Data - Farrah Bostic (The Difference Engine)
   2. Challenges for the Data Ecosystem - Doug Cutting (Cloudera)
   3. When AI joins the team: Onboarding the next generation of employees - Jana Eggers
   4. Data ‘daddying' vs. data empowerment - Tara Hirebet (R/GA)
   5. Taxi Uncle, where are you?: Using machine learning to predict taxi availability - Kevin Lee (GrabTaxi)
   6. Toward Big Data driven network, sponsored by Huawei - Sanqi Li (Huawei)
   7. Drive value faster: New optimizations for Big Data and analytics - Ziya ma (Intel Corp)
   8. Music science: Applying streaming data to map a billion behaviors - Rishi Malhotra (Saavn)
   9. The Next Generation of Analytics - Mike Olson (Cloudera)
   10. Road to real-time digital business - Rod Smith (IBM Emerging Internet Technologies)
   11. Deep Learning - Melanie Warrick (Skymind)
   12. State of Spark, and where it is going - Reynold Xin (Databricks)
2. Data Science and Advanced Analytics
   1. Data science for Telecom - Part 1 - Juliet Hougland (Cloudera), Sandy Ryza (Cloudera)
   2. Data science for Telecom - Part 2 - Juliet Hougland (Cloudera), Sandy Ryza (Cloudera)
   3. Data science for Telecom - Part 3 - Juliet Hougland (Cloudera), Sandy Ryza (Cloudera)
   4. Machine learning In Python with scikit-learn - Part 1 - Andreas Mueller (NYU, scikit-learn)
   5. Machine learning In Python with scikit-learn - Part 2 - Andreas Mueller (NYU, scikit-learn)
   6. Machine learning In Python with scikit-learn - Part 3 - Andreas Mueller (NYU, scikit-learn)
   7. Machine learning In Python with scikit-learn - Part 4 - Andreas Mueller (NYU, scikit-learn)
   8. Interactive data visualization with Lightning: Using d3, Seaborn, and R - Part 1 - Matthew Conlen (FiveThirtyEight)
   9. Interactive data visualization with Lightning: Using d3, Seaborn, and R - Part 2 - Matthew Conlen (FiveThirtyEight)
   10. Interactive data visualization with Lightning: Using d3, Seaborn, and R - Part 3 - Matthew Conlen (FiveThirtyEight)
   11. Deploying models with Azure Machine Learning - Part 1 - Danielle Dean (Microsoft), Wee Hyong Tok (Microsoft)
   12. Deploying models with Azure Machine Learning - Part 2 - Danielle Dean (Microsoft), Wee Hyong Tok (Microsoft)
   13. Deploying models with Azure Machine Learning - Part 3 - Danielle Dean (Microsoft), Wee Hyong Tok (Microsoft)
   14. Building South East Asia's largest E-commerce Recommender - Kai Xin Thia (Lazada)
   15. Apache SINGA: A flexible and scalable deep learning platform for big data analytics - Ju Fan (National University of Singapore) , Wei Wang (National University of Singapore)
   16. Data modeling for data science: Simplify your workload with complex types - Marcel Kornacker (Cloudera, Inc.) , Skye Wanderman-Milne (Cloudera)
   17. Technology solutions for data analytics with privacy and data control - Stephen Hardy (National ICT Australia)
   18. Using EEG and machine learning for lie detection - Jennifer Marsman (Microsoft)
   19. Building and deploying real time big data prediction models - Deepak Agrawal (24[7] Inc.)
   20. Scaling the Python data experience - Wes McKinney (Cloudera)
   21. The revolution of location: Geospatial applications in marketing research - Whye Loon Tung (Nielsen)
   22. Petascale genomics - Uri Laserson (Cloudera)
   23. How to run Neural Nets on GPUs - Melanie Warrick (Skymind)
   24. Enterprise Deep Learning Workflows with DL4J - Josh Patterson (Patterson Consulting)
3. Data-driven Business
   1. Developing a modern enterprise data strategy - Part 1 - Edd Dumbill (Silicon Valley Data Science), John Akred (Silicon Valley Data Science)
   2. Developing a modern enterprise data strategy - Part 2 - Edd Dumbill (Silicon Valley Data Science), John Akred (Silicon Valley Data Science)
   3. Developing a modern enterprise data strategy - Part 3 - Edd Dumbill (Silicon Valley Data Science), John Akred (Silicon Valley Data Science)
   4. Developing a modern enterprise data strategy - Part 4 - Edd Dumbill (Silicon Valley Data Science), John Akred (Silicon Valley Data Science)
   5. Democratizing big data: Riding the curve from descriptive to prescriptive intelligence - Tushar Shanbhag (Adatao, Inc)
   6. Why you need a data strategy - Edd Dumbill (Silicon Valley Data Science)
   7. Building a self-serve real-time reporting platform at LinkedIn - Shirshanka Das (LinkedIn)
   8. Data-savvy leaders of the future: Designing an applied analytics course for MBAs - Hallie Benjamin (Accenture)
   9. The 3 key barriers keeping companies from acting upon the possibilities that big data has to offer - Pauline Brown (Dataiku)
   10. Don't believe everything you see on CSI: Beyond predictive policing - Hong Eng Koh (Oracle) , Vladimir Videnovic (Oracle)
   11. How to tell compelling data stories: Why stories are still important in a data-driven world - Selene Chew (Adatao)
   12. Leveraging data analytics for high performance design - Rakesh Menon (McLaren Applied Technology)
4. Hadoop Platform
   1. Hadoop Application Architectures: Fraud Detection - Part 1 - Gwen Shapira (Confluent), Ted Malaska (Cloudera), Mark Grover (Cloudera), Jonathan Seidman (Cloudera)
   2. Hadoop Application Architectures: Fraud Detection - Part 2 - Gwen Shapira (Confluent), Ted Malaska (Cloudera), Mark Grover (Cloudera), Jonathan Seidman (Cloudera)
   3. Hadoop Application Architectures: Fraud Detection - Part 3 - Gwen Shapira (Confluent), Ted Malaska (Cloudera), Mark Grover (Cloudera), Jonathan Seidman (Cloudera)
   4. Hadoop's storage gap: Resolving transactional access/analytic performance trade-offs with Kudu - Todd Lipcon (Cloudera)
   5. Designing an SQL-on-Hadoop cluster using Impala simulator: A use case for the banking and financial services sector - Jun Liu (Intel) , Zhaojuan Bian (Intel)
   6. Hadoop in the cloud: An architectural how-to - Jairam Ranganathan (Cloudera)
   7. From Oracle to Hadoop: Unlocking Hadoop for your RDBMS with Apache Sqoop and other tools - Guy Harrison (Dell Software)
   8. Evolving from RDBMS to NoSQL + SQL - Jim Scott (MapR Technologies, Inc.)
5. IoT and Real-time
   1. An Introduction to time series with Team Apache - Part 1 - Patrick McFadin (DataStax)
   2. An Introduction to time series with Team Apache - Part 2 - Patrick McFadin (DataStax)
   3. An Introduction to time series with Team Apache - Part 3 - Patrick McFadin (DataStax)
   4. An Introduction to time series with Team Apache - Part 4 - Patrick McFadin (DataStax)
   5. Invigorating the Telco landscape: How telcos can use data assets to create new applications - Amy Shi-Nash (Singtel)
   6. Monitoring traffic in Singapore using telco data - Thomas Holleczek (Singtel)
   7. GearPump: Real time DAG processing at scale - Sean Zhong (Intel)
   8. Application of Spark on analyzing massive GIS data for a large number of mobile objects - Masaru Dobashi (NTT Data Corp.), Yoshitaka Suzuki (IHI Corporation)
   9. Modeling machine failure in the IoT era - Danielle Dean (Microsoft)
   10. Using machine learning to identify fraud on Telecom networks - Arshak Navruzyan (Argyle Data)
   11. Sketching big data with Spark: Randomized algorithms for large-scale data analytics - Reynold Xin (Databricks)
   12. Next-generation platforms for IoT-driven contextual awareness - Markus Kirchberg (OA Labs Pte. Ltd.)
   13. Modeling the smart and connected city of the future with Kafka and Spark - Eric Frenkiel (MemSQL)
   14. Druid: Power Applications to Analyze Sensor Data - Fangjin Yang (Imply)
   15. How to improve mobile radio network planning based on a new big data structure analysis - Vianney Martinez Alcantara (Datameer)
   16. How are your morals? Ethics in algorithms and IoT - Majken Sander (BusinessAnalyst.dk) , Joerg Blumtritt (Datarella™)
6. Production-ready Hadoop
   1. Apache Hadoop operations for production systems - Part 1 - Kathleen Ting (Cloudera), Jonathan Hsieh (Cloudera, Inc), Philip Langdale (Cloudera, Inc.), Kostas Sakellis (Cloudera)
   2. Apache Hadoop operations for production systems - Part 2 - Kathleen Ting (Cloudera), Jonathan Hsieh (Cloudera, Inc), Philip Langdale (Cloudera, Inc.), Kostas Sakellis (Cloudera)
   3. Apache Hadoop operations for production systems - Part 3 - Kathleen Ting (Cloudera), Jonathan Hsieh (Cloudera, Inc), Philip Langdale (Cloudera, Inc.), Kostas Sakellis (Cloudera)
   4. Apache Hadoop operations for production systems - Part 4 - Kathleen Ting (Cloudera), Jonathan Hsieh (Cloudera, Inc), Philip Langdale (Cloudera, Inc.), Kostas Sakellis (Cloudera)
7. Hadoop Beyond
   1. Reliable data propagation between SQL and NoSQL databases using Aesop - Regunath Balasubramanian (Flipkart Internet)
   2. When it absolutely, positively, has to be there: Reliability guarantees in Kafka - Gwen Shapira (Confluent)
   3. Architectural patterns for streaming applications - Ted Malaska (Cloudera) , Mark Grover (Cloudera)
   4. GDELT + BigQuery: Understanding global society through SQL - Felipe Hoffa (Google) , Kalev Leetaru (GDELT Project (http://gdeltproject.org/))
   5. Breakthrough OLAP performance on Cassandra and Spark - Evan Chan (Tuplejump)
   6. Customer record deduplication using Spark and Reifier - Dave Chan (UBM Asia) , Sonal Goyal (Nube)
   7. Estimating financial risk with Spark - Sandy Ryza (Cloudera)
8. Design, User Experience, Visualization
   1. Visualising multi-dimensional data - Amit Kapoor (Narrativeviz Consulting)
9. Sponsored
   1. Patterns from the future - Deepak Ramanathan (SAS Asia Pacific)
   2. The journey to value using advanced analytics - Thomas Beaujard (Accenture Digital) , Tom Ridsdill-Smith (Woodside)
   3. Analytics in action – The analytics lifecycle from data discovery to deployment - Deepak Ramanathan (SAS Asia Pacific)
   4. Road to real-time digital business - Rod Smith (IBM Emerging Internet Technologies)
   5. Hadoop data replication: Guaranteeing consistency across distributions, versions and datacenters while active - Paul Scott-Murphy (WANdisco)
   6. Demystifying analytics: Idea to insight in 7 minutes - Christopher Harrold (EMC)
   7. On the edge of everything – from edge security to edge analytics: Emerging technologies define the way progressive organizations will interact with data - Joanna Schloss (Dell Software)
   8. Avoiding big data ecoming a big problem - Raghunath Nambiar (Cisco Systems)
   9. Scaling document data up (way up) while scaling complexity down - Ted Dunning (MapR)
   10. Big solution in manufacturing industry: Ask hadoop. Hadoop answers. - SeongHwa Ahn (SK telecom) , Jisung Kim (sk telecom)
   11. Faster time to insight using Spark, Tachyon, and Zeppelin - Nirmal Ranganathan (Rackspace Hosting)
   12. SAP HANA Vora: Delivering contextual awareness in the digital enterprise - Paul Marriott and Mark Teehan (SAP Asia Pacific Japan)
   13. Advanced analytics with large scale distributed machine learning on Apache Spark - Shengsheng Huang (Intel)
   14. Achieving business transformation with Open Enterprise Hadoop - Jeff Markham (Hortonworks)
   15. Hadoop everywhere: Geo-distributed storage for big data - Nikhil Joshi (EMC, Advanced Software Division), Priya Lakshminarayanan (EMC Corporation)
10. Security Governance
    1. 12 steps to cloud security - Vishnu Vettrivel (Atigeo)
    2. How to avoid building a "data swamp": Case studies in data management and governance - Mark Donsky (Cloudera) , Naren Koneru (Cloudera)