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    • 5 Traps to Avoid and 5 Ways to Succeed with Big Data Analytics
      5 Traps to Avoid and 5 Ways to Succeed with Big Data Analytics Hal Lavender, Chief Architect, Cognizant, Thomas Dinsmore, BI & Big Data Expert, Josh Klahr, VP Product Management, AtScale D Recorded: Dec 20 2017 6:00 pm UTC 59 mins
    • When it comes to Big Data Analytics, do you know if you are on the right track to succeed in 2017?

      Is Hadoop where you should place your bet? Is Big Data in the Cloud a viable choice? Can you leverage your traditional Big Data investment, and dip your toe in modern Data Lakes too? How are peer and competitor enterprises thinking about BI on Big Data?

      Come learn 5 traps to avoid and 5 best practices to adopt, that leading enterprises use for their Big Data strategy that drive real, measurable business value.

      In this session you’ll hear from Hal Lavender, Chief Architetect of Cognizant Technologies, Thomas Dinsmore, Big Data Analytics expert and author of ‘Disruptive Analytics: Charting Your Strategy for Next-Generation Business Analytics, along with Josh Klahr, VP of Product, as they share real world approaches and achievements from innovative enterprises across the globe.

      Join this session to learn…

      - Why leading enterprises are choosing Cloud for Big Data in 2017
      - What 75% of enterprises plan to drive value out of their Big Data
      - How you can deliver business user access along with security and governance controls

      Read more >
    • The Ideal Architecture for BI on Big Data
      The Ideal Architecture for BI on Big Data Scott Gidley Zaloni - VP of Product Management, Josh Klahr AtScale - VP of Product Recorded: Dec 14 2017 4:00 pm UTC 46 mins
    • Watch this online session and learn how to reconcile the changing analytic needs of your business with the explosive pressures of modern big data.

      Leading enterprises are taking a "BI with Big Data" approach, architecting data lakes to act as analytics data warehouses. In this session Scott Gidley, Head of Product at Zaloni is joined by Josh Klahr, Head of Product at AtScale. They share proven insights and action plans on how to define the ideal architecture for BI on Big Data.

      In this webinar you will learn how to

      - Make data consumption-ready and take advantage of a schema-on-read approach
      - Leverage data warehouse and ETL investments and skillsets for BI on Big Data
      - Deliver rapid-fire access to data in Hadoop, with governance and control

      Read more >
    • Tame the Complexity of Big Data Infrastructure
      Tame the Complexity of Big Data Infrastructure Tony Baer, Big Data Analyst, Ovum; Anant Chintamaneni, VP of Products, BlueData Recorded: Aug 12 2015 5:00 pm UTC 58 mins
    • Implementing Hadoop can be complex, costly, and time-consuming. It can take months to get up and running, and each new user group typically requires their own infrastructure.

      This webinar will explain how to tame the complexity of on-premises Big Data infrastructure. Tony Baer, Big Data analyst at Ovum, and BlueData will provide an in-depth look at Hadoop multi-tenancy and other key challenges.

      Join us to learn:

      - The pitfalls to avoid when deploying Big Data infrastructure
      - Real-world examples of multi-tenant Hadoop implementations
      - How to achieve the simplicity and agility of Hadoop-as-a-Service – but on-premises

      Gain insights and best practices for your Big Data deployment. Find out why data locality is no longer required for Hadoop; discover the benefits of scaling compute and storage independently. And more.

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    • Informatica Big Data Management Deep Dive and Demo
      Informatica Big Data Management Deep Dive and Demo Amit Kara, Big Data Technical Marketing, Informatica Recorded: Jan 28 2016 5:00 pm UTC 62 mins
    • Hadoop is not just for play anymore. Companies that are turning petabytes into profit have realized that Big Data Management is the foundation for successful Big Data projects.

      Informatica Big Data Management delivers the industry’s first and most comprehensive solution to natively ingest, integrate, clean, govern, and secure big data workloads in Hadoop.

      In this webinar you’ll learn through in depth product demos about new features that help you increase productivity, scale and optimize performance, and manage metadata such as:

      • Dynamic Mappings – enables mass ingestion & agile data integration with mapping templates, parameters and rules
      • Smarter Execution Optimization – higher performance with pushdown to DB, auto-partitioning and runtime job execution optimization
      • Blaze – high performance execution engine on YARN for complex batch processing
      • Live Data Map – Universal metadata catalog for users to easily search and discover data properties, patterns, domain, lineage and relationships

      Register today for this deep dive and demo.

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    • Logtrust Real-time Big Data Analytics
      Logtrust Real-time Big Data Analytics Logtrust Big Data Analytics Recorded: Jul 7 2017 3:30 pm UTC 4 mins
    • No Code, Low Code Big Data Analytics from Simple Search to Complex Event Processing.

      Logtrust is designed for fast data exploration and interaction with real-time visualizations on complex data streams and historical data at rest such as:

      - Machine behavior during attacks
      - Network traffic flow analytics
      - Firewall events
      - Application performance metrics
      - Real-time threat hunting and cyber security
      - IoT analytics

      Explore Petabytes of data with Logtrust without worrying about storage costs or indexers, analyze billions of events per day with ultra-low latency queries, and experience unique real-time performance on trillions of events with over +150,000 ingest EPS per core, +1,000,000 search EPS per core, and +65,000 complex event processing EPS per core.

      Live Data Exploration
      Logtrust data is always fresh with real-time data updates in their native formats. Slice and dice subsets of data at any point in time for exploration and deep forensics on real-time data streams.

      Powerful Data Exploration & Analytics
      Accelerate time-to-insights and rich visualizations with simple point and click. Empower your team to quickly harness insights and make faster, smarter decisions. Optionally, use a single compact expressive SQL language (LINQ) and create reusable callable queries for more complex event processing operations.

      Read more >
    • DevOps and Big Data: Rapid Prototyping for Data Science and Analytics
      DevOps and Big Data: Rapid Prototyping for Data Science and Analytics Krishna Mayuram, Lead Architect for Big Data, Cisco; Anant Chintamaneni, VP of Products, BlueData Recorded: Sep 15 2016 5:00 pm UTC 61 mins
    • Join this webinar with Cisco and BlueData to learn how to deliver greater agility and flexibility for Big Data analytics with Big-Data-as-a-Service.

      Your data scientists and developers want the latest Big Data tools for iterative prototyping and dev/test environments. Your IT teams need to keep up with the constant evolution of new tools including Hadoop, Spark, Kafka, and other frameworks.

      The DevOps approach is helping to bridge this gap between other developers and IT teams. Can DevOps agility and automation be applied to Big Data?

      In this webinar, we'll discuss:

      - A way to extend the benefits of DevOps to Big Data, using Docker containers to provide Big-Data-as-a-Service.
      -How data scientists and developers can spin up instant self-service clusters for Hadoop, Spark, and other Big Data tools.
      -The need for next-generation, composable infrastructure to deliver Big-Data-as-a-Service in an on-premises deployment.
      -How BlueData and Cisco UCS can help accelerate time-to-deployment and bring DevOps agility to your Big Data initiative.

      Read more >
    • Shared Infrastructure for Big Data: Separating Compute and Storage
      Shared Infrastructure for Big Data: Separating Compute and Storage Chris Harrold, Global CTO for Big Data, EMC; and Anant Chintamaneni, VP of Products, BlueData Recorded: Dec 8 2015 6:00 pm UTC 63 mins
    • Join this webinar with EMC and BlueData for a discussion on cost-effective, high-performance Hadoop infrastructure for Big Data analytics.

      When Hadoop was first introduced to the market 10 years ago, it was designed to work on dedicated servers with direct-attached storage for optimal performance. This was sufficient at the time, but enterprises today need a modern architecture that is easier to manage as your deployment grows.

      Find out how you can use shared infrastructure for Hadoop – and separate compute and storage – without impacting performance for data-driven applications. This approach can accelerate your deployment and reduce costs, while laying the foundation for a broader data lake strategy.

      Get insights and best practices for your Big Data deployment:
      - Learn why data locality for Hadoop is no longer relevant – we’ll debunk this myth.
      - Discover how to gain the benefits of shared storage for Hadoop, such as data protection and security.
      - Find out how you can eliminate data duplication and run Hadoop analytics without moving your data.
      - Get started quickly and easily, leveraging virtualization and container technology to simplify your Hadoop infrastructure.

      And more. Don't miss this informative webinar with Big Data experts.

      Read more >