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Database Management

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  • Building Enterprise Scale Solutions for Healthcare with Modern Data Architecture Building Enterprise Scale Solutions for Healthcare with Modern Data Architecture Ramu Kalvakuntla, Sr. Principal, Big Data Practice, Clarity Solution Group Recorded: Nov 10 2016 47 mins
    We all are aware of the challenges enterprises are having with growing data and silo’d data stores. Businesses are not able to make reliable decisions with un-trusted data and on top of that, they don’t have access to all data within and outside their enterprise to stay ahead of the competition and make key decisions for their business.

    This session will take a deep dive into current Healthcare challenges businesses are having today, as well as, how to build a Modern Data Architecture using emerging technologies such as Hadoop, Spark, NoSQL datastores, MPP Data stores and scalable and cost effective cloud solutions such as AWS, Azure and BigStep.
  • Data at the corner of SAP and AWS Data at the corner of SAP and AWS Frank Stienhans, CTO, Ocean9 Recorded: Nov 9 2016 48 mins
    Past infrastructures provided compute, storage and network enabling static enterprise deployments which changed every few years. This talk will analyze the consequences of a world where production SAP and Spark clusters including data can be provisioned in minutes with the push of a button.

    What does it mean for the IT architecture of an enterprise? How to stay in control in a super agile world?
  • 3 Critical Data Preparation Mistakes and How-to Avoid them 3 Critical Data Preparation Mistakes and How-to Avoid them Mark Vivien, Business Development, Big Data Recorded: Oct 20 2016 32 mins
    Whether you're just starting out or a seasoned solution architect, developer, or data scientist, there are most likely key mistakes that you've probably made in the past, may be making now, or will most likely make in the future. In fact, these same mistakes are most likely impacting your company's overall success with their analytics program.

    Join us for our upcoming webinar, 3 Critical Data Preparation Mistakes and How to avoid them, as we discuss 3 of the most critical, fundamental pitfalls and more!

    • Importance of early and effective business partner engagement
    • Importance of business context to governance
    • Importance of change and learning to your development methodology
  • Practical Data Cleaning Practical Data Cleaning Lee Baker, CEO, Chi-Squared Innovations Recorded: Oct 13 2016 38 mins
    The basics of data cleaning are remarkably simple, yet few take the time to get organized from the start.

    If you want to get the most out of your data, you're going to need to treat it with respect, and by getting prepared and following a few simple rules your data cleaning processes can be simple, fast and effective.

    The Practical Data Cleaning webinar is a thorough introduction to the basics of data cleaning and takes you through:

    • Data Collection
    • Data Cleaning
    • Data Classification
    • Data Integrity
    • Working Smarter, Not Harder
  • 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