Hi [[ session.user.profile.firstName ]]

Pivotal Best Practices & Technical Demos

  • Date
  • Rating
  • Views
  • Using Advanced Analytics for Better Customer Experience Using Advanced Analytics for Better Customer Experience Hortonworks and Pivotal Recorded: Feb 14 2017 54 mins
    Innovative mobile operators need to mine the vast troves of unstructured data now available to them to help develop compelling customer experiences and uncover new revenue opportunities. In this webinar, you’ll learn how HDB’s in-database analytics enable advanced use cases in network operations, customer care, and marketing for better customer experience. Join us, and get started on your advanced analytics journey today!
  • Cloud Data at epic scale with DataStax Enterprise and Pivotal Cloud Foundry Cloud Data at epic scale with DataStax Enterprise and Pivotal Cloud Foundry Gilbert Lau, Cloud and Big Data Evangelist, DataStax & Pieter Humphrey, Product Marketing, Pivotal Recorded: Feb 9 2017 64 mins
    DataStax Enterprise (DSE) contains a highly distributed NoSQL database - a perfect fit for a highly distributed cloud platform. Pivotal Cloud Foundry makes provisioning access to your existing DSE clusters a self-service exercise for developers and operators. Spring, .NET or any Pivotal Cloud Foundry managed application can then connect and use this Apache Cassandra-based technology as either as OLTP system of record, or read-intensive datastore.

    Join Pieter Humphrey and Gilbert Lau for a brief overview of Cassandra technology, discussion of business benefits and use cases with Pivotal Cloud Foundry, demos of the Pivotal Cloud Foundry Service Broker for DSE, and a look at some proof-of-concept work to deploy a fully BOSH 2.0 managed DSE Tile on Pivotal Cloud Foundry.
  • Using Data Science for Cybersecurity Using Data Science for Cybersecurity Anirudh Kondaveeti and Jeff Kelly Recorded: Jan 17 2017 56 mins
    Enterprise networks are under constant threat. While perimeter security can help keep some bad actors out, we know from experience that there is no 100%, foolproof way to prevent unwanted intrusions. In many cases, bad actors come from within the enterprise, meaning perimeter security methods are ineffective.

    Enterprises, therefore, must enhance their cybersecurity efforts to include data science-driven methods for identifying anomalous and potentially nefarious user behavior taking place inside their networks and IT infrastructure.

    Join Pivotal’s Anirudh Kondaveeti and Jeff Kelly in this live webinar on data science for cybersecurity. You’ll learn how to perform data-science driven anomalous user behavior using a two-stage framework, including using principal components analysis to develop user specific behavioral models. Anirudh and Jeff will also share examples of successful real-world cybersecurity efforts and tips for getting started.

    About the Speakers:
    Anirudh Kondaveeti is a Principal Data Scientist at Pivotal with a focus on Cybersecurity and spatio-temporal data mining. He has developed statistical models and machine learning algorithms to detect insider and external threats and "needle-in-the-hay-stack"​ anomalies in machine generated network data for leading industries.

    Jeff Kelly is a Principal Product Marketing Manager at Pivotal.
  • How to use Apache Zeppelin with Hortonworks HDB How to use Apache Zeppelin with Hortonworks HDB Hortonworks; Pivotal Recorded: Dec 6 2016 26 mins
    Part five in a five-part series, this webcast will be a demonstration of the integration of Apache Zeppelin and Pivotal HDB. Apache Zeppelin is a web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more. This webinar will demonstrate the configuration of the psql interpreter and the basic operations of Apache Zeppelin when used in conjunction with Hortonworks HDB.
  • How to get started with Apache MADlib on Hortonworks HDB How to get started with Apache MADlib on Hortonworks HDB Hortonworks; Pivotal Recorded: Nov 16 2016 31 mins
    Part four in a five-part series, this webcast will be a demonstration of the installation of Apache MADlib (incubating), an open source library for scalable in-database analytics, into Hortonworks HDB. MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical and machine learning methods for structured and unstructured data. This webinar will demonstrate the installation procedures, as well as some basic machine learning algorithms to verify the install.
  • How to manage Hortonworks HDB resources with YARN How to manage Hortonworks HDB resources with YARN Hortonworks; Pivotal Recorded: Oct 19 2016 49 mins
    Part three in a five-part series, this webcast will be a demonstration of the integration of Hortonworks HDB and Apache Hadoop YARN. YARN provides the global resource management for HDB for cluster-level hardware efficiency, while the in-database resource queues and operators provide the database and query-level resource management for workload prioritization and query optimization. This webinar will focus on demonstrating the installation process as well as discuss the various YARN and HDB parameters and best practice settings.
  • How to use PXF with Hortonworks HDB How to use PXF with Hortonworks HDB Hortonworks; Pivotal Recorded: Oct 5 2016 37 mins
    Part two in a five-part series, this webcast will be a demonstration of Pivotal Extension Framework (PXF), an extensible framework that allows Hortonworks HDB to query external system data. This is really useful for both data loading, and also avoiding data loading for data that doesn’t need to reside within the database instance. PXF includes built-in connectors for accessing data inside HDFS files, Hive tables via Catalog, and HBase tables.
  • How to Install Hortonworks HDB on Hortonworks HDP How to Install Hortonworks HDB on Hortonworks HDP Hortonworks; Pivotal Recorded: Sep 21 2016 63 mins
    This webcast is the first in a five-part series on Hortonworks HDB, demonstrating the installation procedures for installing Hortonworks HDB on Hortonworks HDP. HDB’s integration with Apache Ambari allows you to install and manage your high-performance SQL database alongside other Hadoop services. Starting with an existing HDP cluster, it will cover any required prerequisites and then leveraging Apache Ambari to complete the install.
  • High-Performance Interactive SQL Analytics and Machine Learning on Hadoop High-Performance Interactive SQL Analytics and Machine Learning on Hadoop Jeff Kelly; Pivotal | Ajay Singh;; Hortonworks Recorded: Sep 7 2016 64 mins
    Already strategic partners, Pivotal Software and Hortonworks deepened their relationship in Spring 2016 with the goal of providing enterprises the most complete modern data platform for advanced analytics and machine learning. As part of the expanded relationship, Hortonworks has introduced Hortonworks HDB, the market’s leading Hadoop Native SQL database and big data SQL machine learning engine based on Apache HAWQ and Apache MADlib (incubating).

    Join Pivotal’s Jeff Kelly and Hortonworks’ Ian Fyfe in this webinar to learn more about:
    • Advantages of Hortonworks HDB
    • How it works
    • When to consider HDB vs. Apache Hive
    • HDB industry use cases

Embed in website or blog