July 2018: Real Time Databases

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Presented by Woody Christy

Kinetica

Modern business is fluid.  Critical business events must be responded to when they occur.  Delays mean lost opportunities and sub-optimal outcomes.  Modern analytics must be as agile as the business itself.

The days of looking at your data in the rear-view mirror are coming to an end.  We are at the dawn of a new analytic revolution:  the real-time database.

Millisecond latency is the new analytic performance standard.  A new class of GPU-accelerated databases enable this level of performance.  GPU-accelerated databases are over 100x more performant than even the “fastest” in-memory data stores.

GPU-accelerated databases can provide extreme levels of scalability without negative performance impacts.  They are also easy to implement; thanks to their use of ANSI-standard SQL and hybrid visualization capabilities.  This makes them particularly attractive for some of the most demanding analytic tasks; like scoring of predictive models, and geospatial visualizations.

Join Woody Christy from Kinetica to learn how GPUaccelerated databases can enable real-time businesses.

 

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June 2018: Data Management for the Internet of Things

Presented by Michael Scofield, M.B.A.

Assistant Professor, Loma Linda University

The “internet of things” is dependent upon the communication between various devices—such communication containing data. When data moves, it has architecture, and it is that architecture of “data in motion” (albeit small records within a transaction) which must be astutely designed.

The quality of any business or industrial process outcomes depend upon three major foundations:

  1. Quality and reliability of hardware (and physical network) supporting it.
  2. Quality of design of the process and decision rules. This includes anticipating all contingencies which would influence a decision made independent of human judgment and involvement.
  3. Quality of the data at capture, and quality of definition and clarity of data conveyed between devices.

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March 2018: Data Science Career Path

Presented by Asoka Diggs

Intel Corporation

UPDATED: A PDF of Asoka’s presentation is available for download.

Many are interested in data science as a career. In this presentation, we’ll break data science down into smaller pieces that can be better understood and might help you with deciding if some or all of data science is a career path that you want to pursue. We’ll also get into some of the additional skills critical to success as a data scientist with the objective of being effective and/or contribute meaningfully to a data science project, and not just get the job title.

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