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Database Management

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  • Self-service BI for SAP and HANA – Dream or Reality? Self-service BI for SAP and HANA – Dream or Reality? Swen Conrad, CEO, Ocean9 Recorded: Sep 14 2016 48 mins
    Gartner predicts that “analytics will be pervasive … for decisions and actions across the business.” Sounds like analytics nirvana with instant access for any analysis you want to do, in other words self-service BI. Is this dream or reality?

    Join this webinar to find out how clouds like AWS or Azure are moving the industry close to this nirvana today through simple assembly of cloud services combined with the appropriate consumption model of these services.

    We will demonstrate how easy it is to provision your high end SAP HANA Database right next to your BI Analytics tier.

    Maybe we are closer to this nirvana than you think?
  • The Role of FPGAs in SparK Accelerators The Role of FPGAs in SparK Accelerators Shreyas Shah, Principal Data center Architect, Xilinx Recorded: Aug 29 2016 61 mins
    In the cloud computing era, data growth is exponential. Every day billions of photos are shared and large amount of new data created in multiple formats. Within this cloud of data, the relevant data with real monetary value is small. To extract the valuable data, big data analytics frame works like SparK is used. This can run on top of a variety of file systems and data bases. To accelerate the SparK by 10-1000x, customers are creating solutions like log file accelerators, storage layer accelerators, MLLIB (One of the SparK library) accelerators, and SQL accelerators etc.

    FPGAs (Field Programmable Gate Arrays) are the ideal fit for these type of accelerators where the workloads are constantly changing. For example, they can accelerate different algorithms on different data based on end users and the time of the day, but keep the same hardware.

    This webinar will describe the role of FPGAs in SparK accelerators and give SparK accelerator use cases.
  • Using Predictive Analytics to optimize Application operations: Can you dig it? Using Predictive Analytics to optimize Application operations: Can you dig it? Lesley-Anne Wilson, Group Product Rollout & Support Engineer, Digicel Group Recorded: Jul 22 2016 23 mins
    Many studies have been done on the benefits of Predictive Analytics on customer engagement in order to change customer behaviour. However, the side less romanticized is the benefit to IT operations as it is sometimes difficult to turn the focus from direct revenue impacting gain to the more indirect revenue gains that can come from optimization and pro-active issue resolution.

    I will be speaking, from an application operations engineers perspective, on the benefits to the business of using Predictive Analytics to optimize applications.
  • Predictive and Prescriptive Power Discovery from Fast, Wide, Deep Big Data Predictive and Prescriptive Power Discovery from Fast, Wide, Deep Big Data Kirk Borne, Principal Data Scientist, Booz Allen Hamilton Recorded: Jul 22 2016 45 mins
    I will summarize the stages of analytics maturity that lead an organization from traditional reporting (descriptive analytics: hindsight), through predictive analytics (foresight), and into prescriptive analytics (insight). The benefits of big data (especially high-variety data) will be demonstrated with simple examples that can be applied to significant use cases.

    The goal of data science in this case is to discover predictive power and prescriptive power from your data collections, in order to achieve optimal decisions and outcomes.
  • Live Webinar: Overcoming the Storage Challenges Cassandra and Couchbase Create Live Webinar: Overcoming the Storage Challenges Cassandra and Couchbase Create George Crump, Storage Switzerland Recorded: Jun 30 2016 53 mins
    NoSQL databases like Cassandra and Couchbase are quickly becoming key components of the modern IT infrastructure. But this modernization creates new challenges – especially for storage. Storage in the broad sense. In-memory databases perform well when there is enough memory available. However, when data sets get too large and they need to access storage, application performance degrades dramatically. Moreover, even if enough memory is available, persistent client requests can bring the servers to their knees.

    Join Storage Switzerland and Plexistor where you will learn:

    1. What is Cassandra and Couchbase?
    2. Why organizations are adopting them?
    3. What are the storage challenges they create?
    4. How organizations attempt to workaround these challenges.
    5. How to design a solution to these challenges instead of a workaround.
  • Big-Data-as-a-Service: On-Demand Elastic Infrastructure for Hadoop and Spark Big-Data-as-a-Service: On-Demand Elastic Infrastructure for Hadoop and Spark Kris Applegate, Big Data Solution Architect, Dell; Tom Phelan, Chief Architect, BlueData Recorded: Jun 22 2016 56 mins
    Watch this webinar to learn about Big-Data-as-a-Service from experts at Dell and BlueData.

    Enterprises have been using both Big Data and Cloud Computing technologies for years. Until recently, the two have not been combined.

    Now the agility and efficiency benefits of self-service elastic infrastructure are being extended to big data initiatives – whether on-premises or in the public cloud.

    In this webinar, you’ll learn about:

    - The benefits of Big-Data-as-a-Service – including agility, cost-savings, and separation of compute from storage
    - Innovations that enable an on-demand cloud operating model for on-premises Hadoop and Spark deployments
    - The use of container technology to deliver equivalent performance to bare-metal for Big Data workloads
    - Tradeoffs, requirements, and key considerations for Big-Data-as-a-Service in the enterprise
  • The Big Data decision path incorporating SAP landscapes The Big Data decision path incorporating SAP landscapes Swen Conrad, CEO, Ocean9 Recorded: Jun 8 2016 49 mins
    Leading companies derive big data technology choices from business needs instead of technology merits. With the variety of possible use cases, either Hadoop, Spark or SAP HANA may provide the best fit to solve business challenges and create value.

    Sounds easy, but managing a variety of big data solutions within a single company puts a skills and cost premium on the organization.

    This session will guide you to the right big data technology according to business needs and highlights the fastest path to adoption.
  • Case Study in Big Data and Data Science: University of Georgia Case Study in Big Data and Data Science: University of Georgia Shannon Quinn, Assistant Professor at University of Georgia; and Nanda Vijaydev, Director of Solutions Management at BlueData Recorded: May 11 2016 61 mins
    Join this webinar to learn how the University of Georgia (UGA) uses Apache Spark and other tools for Big Data analytics and data science research.

    UGA needs to give its students and faculty the ability to do hands-on data analysis, with instant access to their own Spark clusters and other Big Data applications.

    So how do they provide on-demand Big Data infrastructure and applications for a wide range of data science use cases? How do they give their users the flexibility to try different tools without excessive overhead or cost?

    In this webinar, you’ll learn how to:

    - Spin up new Spark and Hadoop clusters within minutes, and quickly upgrade to new versions

    - Make it easy for users to build and tinker with their own end-to-end data science environments

    - Deploy cost-effective, on-premises elastic infrastructure for Big Data analytics and research
  • Using the Cloud for Speed-of-Thought Analytics on All Your Data Using the Cloud for Speed-of-Thought Analytics on All Your Data Snowflake Computing, Ask.com, Tableau Recorded: Apr 28 2016 64 mins
    1.5 TB of data per day? No problem! Learn how Ask.com turned to Snowflake’s cloud-native data warehouse combined with Tableau’s data visualization solution to address their challenges.

    Ask.com and its parent family of premium websites operate in an extremely competitive environment. To stand out in the crowd, the huge amounts of data generated by these websites needs to be analyzed to understand and monetize a wide variety of site traffic.

    Their challenges:
    Ask.com’s previous solution of Hadoop + a traditional data warehouse was limiting their analysts’ ability to bring together and analyze their data.
    - Significant amounts of custom processing to bring together data
    - Performance issues for data users due to concurrency and contention challenges
    - Several hours to incorporate new data into analytics.

    Join Ask.com, Snowflake Computing, and Tableau for an informative webinar where you’ll learn:
    - How Ask.com simplified their data infrastructure by eliminating the need for Hadoop + a traditional data warehouse
    - Why Ask.com’s analysts are able to explore and analyze data without the frustration of poor, inconsistent performance
    - How Ask.com’s widely distributed team of analysts can now access a single comprehensive view of data for better insights
  • CapSpecialty - Leveraging Data to Deliver Faster Business Results Linked to KPIs CapSpecialty - Leveraging Data to Deliver Faster Business Results Linked to KPIs MicroStrategy, Snowflake and CapSpecialty Recorded: Apr 27 2016 47 mins
    CapSpecialty is upping its game to become the preferred provider of specialty insurance products using MicroStrategy Analytics and Snowflake Cloud Data Warehousing.

    CapSpecialty’s investment to overhaul its data pipeline and management systems has delivered fast and measurable results. The stage has been set for CapSpecialty executives to view dashboards that display real-time profitability and KPIs. Insurance analysts and underwriters have self-service access to 10 years’ worth of governed data, allowing them to analyze customer trends and view product performance by category, geography, and agent. CapSpecialty is witnessing measurable business results from the engines that power their BI environment: MicroStrategy enterprise analytics platform firmly integrated with Snowflake’s cloud-based elastic data warehouse.

    Attend this webcast to learn how CapSpecialty has combined enterprise analytics with an elastic cloud-based data warehouse, a solution that serves as the cornerstone of their agile, metrics-focused culture.

    Join us live!

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