#BDM 66 Running Real-time Machine Learning Analytics On Traces by Fawaz Ghali

Big Data Montreal would like to invite you to its 66th meeting!
LOCATION: TBD

Join us on Thursday Feb 23th 2022 at 6:00PM to attend a conference, as well as to network with other Big Data enthusiasts from Montreal!
All are welcome, no matter if you already have some experience with Big Data technologies or if you're simply curious to learn more.
We have 2 presentations scheduled (flash and a main one):

1. The Ultimate trick to learn faster (AI apply to life, 10-15 mins) by Francis Pieraut - Chief AI Enabler@SiliconIsland.ai
2. Running Real-time Machine Learning Analytics On Traces (45-60 mins) by Fawaz Ghali, Principal Developer Advocate

Title:
Running Real-time Machine Learning Analytics On Traces

Abstract:
Let’s do things differently. To start with, let us view logs and traces as no different from any other data. The data an application indirectly generates when in use (the logs and traces) is no different from the data an application directly works with (input and output). So let’s keep them all together in a scalable cloud storage repository. Once it is there, it is just like any other big data. We need to analyze and apply intelligent monitoring to detect situations of interest. So we need to apply trained Real-time ML models to a stream of such data for immediate alerting when the traces indicate an unwanted behavior occurring or brewing. This talk will show how to harness existing technologies to do just that.

Bio:
Fawaz Ghali is a Principal Developer Advocate at Hazelcast with 20+ years of experience in software development, machine learning and real-time intelligent applications. He holds a PhD in Computer Science and has worked in the private sector as well as Academia as a Researcher and Senior Lecturer. He has published over 46 scientific papers in the fields of machine learning and data science. His strengths and skills lie within the fields of low latency applications, IoT & Edge, distributed systems and cloud technologies.