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Philipp
Philipp Drieger

Philipp Drieger works as a Principal Machine Learning Architect at Splunk. He accompanies Splunk customers and partners across various industries in their digital journeys, helping to achieve advanced analytics use cases in cybersecurity, IT operations, IoT and business analytics. Before joining Splunk, Philipp worked as freelance software developer and consultant focussing on high performance 3D graphics and visual computing technologies. In research, he has published papers on text mining and semantic network analysis.

Platform 5 Min Read

Chasing a Hidden Gem: Graph Analytics with Splunk’s Machine Learning Toolkit

This article tells you, how you can mine hidden gems within your data and eventually dig out that precious diamond you've been trying to find for a long time.
Platform 3 Min Read

Predicting and Preventing Crime with Machine Learning - Part 2

There are many ways to use machine learning to predict and prevent crime. In this article we take a closer look at how London crime rates can be predicted.
Platform 3 Min Read

Predicting and Preventing Crime with Machine Learning - Part1

Using technology to make the world a better place is not an unattainable vision anymore. Machine learning can help predict and prevent crime.
Platform 2 Min Read

AI in Logistics Hackathon with BMW Group and Splunk

60 students from 7 different Lebanese universities competed to solve an “AI in Logistics” use case
IT 2 Min Read

Using machine learning for anomaly detection research

Anomalies vary by use case–IT system outages, security breaches, business analytic patterns, IoT device status. Set baselines & learn means of spotting anomalies with Splunk.
Industries 2 Min Read

Turn IoT sensor data into Operational Intelligence for logistics

Splunk Operational IT & Analytics for IoT applied to use case that tracks damage, anomalies and incidents to high quality goods while in transit.