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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February 2018: Business Applications of Blockchain Technology

Presented by Mark Wheeler

UPDATED: A PDF of the presentation is available for download.

Blockchain technology is being talked about as one of the next big innovations to take hold across multiple industries. Businesses who focus on transactions, contracts, and assets management are just a few of the initial sectors of the economy which will be disrupted. As the underlying technology begins to take hold, time-consuming and labor-intensive functions will be replaced by automated and “always on” smart processes. Centralized models of trust and authenticity will be replaced by decentralized services and crowd-based consensus algorithms.

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