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 GPU–accelerated 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.

May 2018: All Those Other Important Parts of Data Modeling: Security, Privacy and More

Presented by Karen Lopez

Senior Project Manager and Architect at InfoAdvisors

Modern database systems have introduced more support for security, privacy and compliance over the last few years. We expect this to increase as compliance issues such as GDPR and other data compliance challenges arise.

In this session, Karen will be discussing the newer features from a database designers points of view, including:

• Data Masking
• End-to-end Encryption
• Row Level Security
• New Data Types
• Data Categorization and Classification

We’ll look at the new features, why you should consider them, where they work, where they don’t, who needs to be involved in using them, and what changes, if any, need to be made to applications or tools that you support.

Speaker

Karen is a senior data architect with an extensive background in development processes and data management. She specializes in taking practical approaches to solutions development. Karen has helped many IT organizations choose appropriate methods and standards based on the group’s culture, experience, and focus. She is an international speaker on modern development and design processes, specializing in engaging, often irreverent presentations on data and career-related topics. She blogs at datamodel.com and can be found on Twitter @datachick.

April 2018: The Metadata Catalog and the Modern Data Lake

Presented by Andrew Ahn

VP Product Management, Waterline Data

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

Learn how to leverage metadata and Spark to manage traditional data sources in the modern data lake. We will also look at Waterline Data’s approach to discover and understand relational databases, Hive, HDFS, and blob stores.

Speaker

Prior to Waterline, Andrew Ahn was Director of Project Management, Governance at Hortonworks, covering Apache Falcon and Apache Atlas technologies and products. He was as also an Apache Atlas committer. Prior work includes product and governance duties for the NYSE Euronext where he worked in the Chief Data Office and was responsible for the product development roadmap.

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.