Strata Hadoop World NY 2016 - Enterprise adoption Track
Strata Hadoop World NY 2016 had following interestinig talks in its Enterprise adoption sessions
Deploying and managing Hive, Spark, and Impala in the public cloud by Andrei Savu and Vinithra Varadharajan and Jennifer Wu and Matthew Jacobs
Public cloud usage for Hadoop workloads is accelerating. Consequently, Hadoop components have adapted to leverage cloud infrastructure. Andrei Savu, Vinithra Varadharajan, Matthew Jacobs, and Jennifer Wu explore best practices for Hadoop deployments in the public cloud and provide detailed guidance for deploying, configuring, and managing Hive, Spark, and Impala in the public cloud.
Using graph databases to operationalize insights from big data by Emil Eifrem and Tim Williamson
Tim Williamson and Emil Eifrem explain how organizations can use graph databases to operationalize insights from big data, drawing on the real-life example of Monsanto’s use of graph databases to conduct real-time graph analysis of the company’s data to transform the business in ways that were previously impossible.
Big data in healthcare by Taposh Roy and Rajiv Synghal and Sabrina Dahlgren
While other industries have embraced the digital era, healthcare is still playing catch-up. Kaiser Permanente has been a leader in healthcare technology and first started using computing to improve healthcare results in the 1960s. Taposh Roy, Rajiv Synghal, and Sabrina Dahlgren offer an overview of Kaiser’s big data strategy and explain how other organizations can adopt similar strategies.
Building data lakes in the cloud by Alex Bordei
Alex Bordei walks you through the steps required to build a data lake in the cloud and connect it to on-premises environments, covering best practices in architecting cloud data lakes and key aspects such as performance, security, data lineage, and data maintenance. The technologies presented range from basic HDFS storage to real-time processing with Spark Streaming.
Swipe, dip, and hover: Managing card payment data at Visa by Nandu Jayakumar
Visa, the world’s largest electronic payments network, is transforming the way it manages data: database appliances are giving way to Hadoop and HBase; proprietary ETL technologies are being replaced by Spark; and enterprise warehouse data models will be complemented by flexible data schemas. Nandu Jayakumar explores the adoption of big data practices at a conservative, financial enterprise.
A unified ecosystem for market data visualization by Janaki Parameswaran and Kishore Ramachandran
FINRA ingests over 50 billion records of stock market trading data daily into multipetabyte databases. Janaki Parameswaran and Kishore Ramachandran explain how FINRA technology integrates data feeds from disparate systems to provide analytics and visuals for regulating equities, options, and fixed-income markets.
BI and SQL analytics with Hadoop in the cloud by Henry Robinson and Justin Erickson
Henry Robinson and Justin Erickson explain how to best take advantage of the flexibility and cost-effectiveness of the cloud with your BI and SQL analytic workloads using Apache Hadoop and Apache Impala (incubating), covering the architectural considerations, best practices, tuning, and functionality available when deploying or migrating BI and SQL analytic workloads to the cloud.
Big data is a household word: How Procter & Gamble uses on-cluster Hadoop BI to give visual insight to hundreds of business users for everyday use by terry mcfadden and Priyank Patel
Terry Mcfadden and Priyank Patel discuss Procter and Gamble's three-year journey to enable production applications with on-cluster BI technology, exploring in detail the architecture challenges and choices made by the team along this journey.
Life of a click: How Hearst manages clickstream analytics in the cloud by Rick McFarland
Rick McFarland explains how the Hearst Corporation utilizes big data and analytics tools like Spark and Kinesis to stream click data in real-time from its 300+ websites worldwide. This streaming process feeds an editorial tool called Buzzing@Hearst, which provides instant feedback to authors on what is trending across the Hearst network.
Machine intelligence in the wild: How AI will reshape global industries by David Beyer
Society is standing at the gates of what promises to be a profound transformation in the nature of work, the role of data, and the future of the world's major industries. Intelligent machines will play a variety of roles in every sector of the economy. David Beyer explores a number of key industries and their idiosyncratic journeys on the way to adopting AI.