Big Data and Machine Learning - London - Meetup #4

Tuesday, May 23, 2017 - 18:30
Big Data and Machine Learning - London

Meetup #4

PLEASE NOTE: Limit of 80 attendees (see below)

Welcome to Meetup #4, and what we hope will be another interesting evening of presentations and lightning talks.  You are encouraged to participate in the Q&A session and hope that the networking gives you the opportunity to meet with the presenters, other attendees and the organisers of the Meetup.

The agenda is listed below, followed by further details about the main presentations and their presenters.

Looking forward to meeting many of you at this Meetup, and for those who are unable to join us, hope to see you at one of our other meetups throughout the year.

Please also note that there is a maximum limit of 80 attendees for this event.  However, in common with other Meetups, we unfortunately see quite a high no-show rate (despite pleading with people to release their places if they find they are unable to attend).  We have decided to raise the number of attendees who can register to 120, in the hope that we can get closer to a full-house.  We will however have to stick to a maximum of 80 through the doors.  So on the night, it will be on a first come, first served.  So make sure you turn up early to guarantee entry! 

If you have already RSVP’d “YES”, but find you are no longer able to attend, please make the effort to release your space ASAP to enable those on the Waiting List the opportunity to attend – THANKS!

Should you wish to contact me, email me at [masked].

Kindest regards



18:30  Drinks reception and networking

18:55  Welcome (5 mins)

19:00  Fast Track to Machine Learning using Splunk

            Idris Sober

            (30 mins)

19:30  Snowflake Overview

            Nicolas Baret

            (30 mins)

20:00  The Lab Series

               Mark Whalley

             (30 mins)

20:30  Networking

21:30   Close


Fast Track to Machine Learning using Splunk

An introduction on how to quickly setup & play around with machine learning without any prior experience; Ideal for those who want to apply ML to their data without writing a single line of code. Aimed at those who are interested in data science but don’t have relevant programming experience.

Idris Sober

Idris is a Security Consultant at ECS.  Helping customers to drive complex deployments of Splunk while working side by side with technical teams to solve their unique problems across different use cases.


Provides consultancy services from managing Cyber Security to DevOps. Setting clear strategies to help enterprise customers reach their business goals through technology solutions


Snowflake Overview

Snowflake is a data warehouse platform born in the cloud, the only one of its kind.

A high-level/marketing presentation and technical deep dive with use cases to highlight the problems we address.

Nicolas Baret

Director of Sales Engineering at Snowflake Europe. He has 20 years’ experience in the DW and BI space, in consulting and pre-sales.

Having worked for companies like SAS, Teradata, Tibco Spotfire, Talend, and have a broad exposure to the data space.


The Lab Series

In this continuation of The Lab Series, Mark will outline the next phase of the Mini Project for capturing Automatic Dependent Surveillance Broadcast (ADS-B) to track the position, speed and other metrics of commercial aircraft. 

So far we have discussed the background to ADS-B, and how to install and configure DUMP1090 to capture and decode the digital broadcast signals from aircraft transponders.  This was followed by a session which introduced the various outputs from DUMP1090, and outlined a method for transforming and feeding this data into Kafka topics.

This session will demonstrate how, using Vertica’s inbuilt tools for integrating with Apache Kafka, we can populate a series of Vertica tables in near real time, and make this data immediately available for querying and analytics.

As previously discussed, The Lab Series presentations at the F2F Meetups are primarily intended to discuss what is happening in the Mini Projects that are covered in more detail during the ONLINE Meetup events.  These ONLINE events have been recorded and are available on request.

Further details of The Lab Series can be found on the Agenda of Meetup #1.

Mark Whalley

From the early 1980s, Mark worked with Michael Stonebraker's Ingres RDBMS and then column-store big data analytic technologies. In 2016, he joined HPE Big Data Platform as a Systems Engineer specialising in Vertica and Vertica SQL in Hadoop.

Hewlett Packard Enterprise, 1 Aldermanbury Square