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Data Management

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  • Emerging Memory Poised to Explode
    Emerging Memory Poised to Explode
    Moderator: Alex McDonald, SNIA SSSI Co-Chair; Presenters: Tom Coughlin, Coughlin Associates & Jim Handy, Objective Analysis Recorded: Dec 11 2018 58 mins
    Join SSSI members and respected analysts Tom Coughlin and Jim Handy for a look into their new Emerging Memory and Storage Technologies Report. Tom and Jim will examine emerging memory technologies and their interaction with standard memories, how a new memory layer improves computer performance, and the technical advantages and economies of scale that contribute to the enthusiasm for emerging memories. They will provide an outlook on market projections and enabling and driving applications. The webcast is the perfect preparation for the 2019 SNIA Persistent Memory Summit January 24, 2019.
  • Take the Leap to SNIA’s Storage Management Initiative Specification 1.8
    Take the Leap to SNIA’s Storage Management Initiative Specification 1.8
    Mike Walker, former Chair SNIA SMI TWG and former IBM Engineer, Don Deel, SNIA SMI Board Chair, SMI TWG Chair, NetApp Recorded: Dec 5 2018 36 mins
    If you’re a storage equipment vendor, management software vendor or end-user of the ISO approved SNIA Storage Management Initiative Specification (SMI-S), you won’t want to miss this presentation. Enterprise storage industry expert Mike Walker will provide an overview of new indications, methods, properties and profiles of SMI-S 1.7 and the newly introduced version, SMI-S 1.8. If you haven’t yet made the jump to SMI-S 1.7, Walker will explain why it’s important to go directly to SMI-S 1.8.
  • The 100-Year Archive Survey Results 2007-2017
    The 100-Year Archive Survey Results 2007-2017
    Sam Fineberg, Thomas Rivera, Bob Rogers Recorded: Oct 10 2018 60 mins
    The Long Term Retention Technical Working Group and the Data Protection Committee will review the results of the 2017 100-year archive survey. In addition to the survey results, the presentation will cover the following topics:
    · How the use of storage for archiving has evolved in ten years
    · What type of information is now being retained and for how long
    · Changes in corporate practices
    · Impact of technology changes such as Cloud
  • Centralized vs. Distributed Storage
    Centralized vs. Distributed Storage
    John Kim, Mellanox; Alex McDonald, NetApp; J Metz, Cisco Recorded: Sep 11 2018 63 mins
    In the history of enterprise storage there has been a trend to move from local storage to centralized, networked storage. Customers found that networked storage provided higher utilization, centralized and hence cheaper management, easier failover, and simplified data protection, which has driven the move to FC-SAN, iSCSI, NAS and object storage.

    Recently, distributed storage has become more popular where storage lives in multiple locations but can still be shared. Advantages of distributed storage include the ability to scale-up performance and capacity simultaneously and--in the hyperconverged use case--to use each node (server) for both compute and storage. Attend this webcast to learn about:
    •Pros and cons of centralized vs. distributed storage
    •Typical use cases for centralized and distributed storage
    •How distributed works for SAN, NAS, parallel file systems, and object storage
    •How hyperconverged has introduced a new way of consuming storage

    After the webcast, please check out our Q&A blog http://bit.ly/2xSajxJ
  • RoCE vs. iWARP
    RoCE vs. iWARP
    Tim Lustig, Mellanox; Fred Zhang, Intel; John Kim, Mellanox Recorded: Aug 22 2018 64 mins
    Network-intensive applications, like networked storage or clustered computing, require a network infrastructure with high bandwidth and low latency. Remote Direct Memory Access (RDMA) supports zero-copy data transfers by enabling movement of data directly to or from application memory. This results in high bandwidth, low latency networking with little involvement from the CPU.

    In the next SNIA ESF “Great Storage Debates” series webcasts, we’ll be examining two commonly known RDMA protocols that run over Ethernet; RDMA over Converged Ethernet (RoCE) and IETF-standard iWARP. Both are Ethernet-based RDMA technologies that reduce the amount of CPU overhead in transferring data among servers and storage systems.

    The goal of this presentation is to provide a solid foundation on both RDMA technologies in a vendor-neutral setting that discusses the capabilities and use cases for each so that attendees can become more informed and make educated decisions.

    Join to hear the following questions addressed:

    •Both RoCE and iWARP support RDMA over Ethernet, but what are the differences?
    •Use cases for RoCE and iWARP and what differentiates them?
    •UDP/IP and TCP/IP: which uses which and what are the advantages and disadvantages?
    •What are the software and hardware requirements for each?
    •What are the performance/latency differences of each?

    Join our SNIA experts as they answer all these questions and more on this next Great Storage Debate

    After you watch the webcast, check out the Q&A blog http://bit.ly/2OH6su8
  • Cloud Mobility and Data Movement
    Cloud Mobility and Data Movement
    Eric Lakin, University of Michigan; Michelle Tidwell, IBM; Alex McDonald, NetApp Recorded: Aug 7 2018 60 mins
    We’re increasingly in a multi-cloud environment, with potentially multiple private, public and hybrid cloud implementations in support of a single enterprise. Organizations want to leverage the agility of public cloud resources to run existing workloads without having to re-plumb or re-architect them and their processes. In many cases, applications and data have been moved individually to the public cloud. Over time, some applications and data might need to be moved back on premises, or moved partially or entirely from one cloud to another.

    That means simplifying the movement of data from cloud to cloud. Data movement and data liberation – the seamless transfer of data from one cloud to another – has become a major requirement.

    In this webcast, we’re going to explore some of these data movement and mobility issues with real-world examples from the University of Michigan. Register now for discussions on:

    •How do we secure data both at-rest and in-transit?
    •Why is data so hard to move? What cloud processes and interfaces should we use to make data movement easier?
    •How should we organize our data to simplify its mobility? Should we use block, file or object technologies?
    •Should the application of the data influence how (and even if) we move the data?
    •How can data in the cloud be leveraged for multiple use cases?
  • How to Leverage Big Data for Customers: Lessons from a Purpose-Driven Bank
    How to Leverage Big Data for Customers: Lessons from a Purpose-Driven Bank
    Paul Clark, CTO, Tandem Recorded: Jul 17 2018 42 mins
    For years, banks have been sitting on a goldmine of customer data. Only recently have they started exploiting that, although not surprisingly for their own benefit.
    Personal data can give great insights to drive bank outcomes by decreasing credit losses and reducing fraud losses. In this webinar Paul Clark, CTO, will look at how we can use customer data to;
    * Drive customer’s own advantage
    * Avoid slip ups
    * Dodge nasty charges
    * Optimise the customer’s finances end to end.
  • Nemertes Conversations: Is Your Data Ready for GDPR?
    Nemertes Conversations: Is Your Data Ready for GDPR?
    Co-presented by: Julie McCoy, Solutions Engineer, AvePoint; and Irwin Lazar, VP & Service Director, Nemertes Research Recorded: May 24 2018 53 mins
    GDPR requires organizations to identify, classify, and protect personal information, but how do you prepare and protect against a possible breach if you don't know what data you have, where it lives, or how it's classified?

    In this informative webinar we'll discuss:
    • GDPR data classification requirements
    • How to incorporate GDPR data analysis into your breech prevention and reaction plan
    • How to classify and protect information across multiple data stores
    • Solutions for automating classification and information protection

    We look forward to sharing this information with you!
  • Does it matter if an algorithm can't explain how it knows what it knows?
    Does it matter if an algorithm can't explain how it knows what it knows?
    Beau Walker, Founder, Method Data Science Recorded: May 24 2018 34 mins
    With the General Data Protection Regulation (GDPR) becoming enforceable in the EU on May 25, 2018, many data scientists are worried about the impact that this regulation and similar initiatives in other countries that give consumers a "right to explanation" of decisions made by algorithms will have on the field of predictive and prescriptive analytics.

    In this session, Beau will discuss the role of interpretable algorithms in data science as well as explore tools and methods for explaining high-performing algorithms.

    Beau Walker has a Juris Doctorate (law degree) and BS and MS Degrees in Biology and Ecology and Evolution. Beau has worked in many domains including academia, pharma, healthcare, life sciences, insurance, legal, financial services, marketing, and IoT.
  • Semantic AI: Bringing Machine Learning and Knowledge Graphs Together
    Semantic AI: Bringing Machine Learning and Knowledge Graphs Together
    Kirk Borne, Principal Data Scientist, Booz Allen Hamilton & Andreas Blumauer, CEO, Managing Partner Semantic Web Company Recorded: May 23 2018 64 mins
    Implementing AI applications based on machine learning is a significant topic for organizations embracing digital transformation. By 2020, 30% of CIOs will include AI in their top five investment priorities according to Gartner’s Top 10 Strategic Technology Trends for 2018: Intelligent Apps and Analytics. But to deliver on the AI promise, organizations need to generate good quality data to train the algorithms. Failure to do so will result in the following scenario: "When you automate a mess, you get an automated mess."

    This webinar covers:

    - An introduction to machine learning use cases and challenges provided by Kirk Borne, Principal Data Scientist at Booz Allen Hamilton and top data science and big data influencer.
    - How to achieve good data quality based on harmonized semantic metadata presented by Andreas Blumauer, CEO and co-founder of Semantic Web Company and a pioneer in the application of semantic web standards for enterprise data integration.
    - How to apply a combined approach when semantic knowledge models and machine learning build the basis of your cognitive computing. (See Attachment: The Knowledge Graph as the Default Data Model for Machine Learning)
    - Why a combination of machine and human computation approaches is required, not only from an ethical but also from a technical perspective.

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