In this Intel Business episode, hosted by Darren Pulsipher, Chief Solutions Architect at Intel Corporation, Adrian Kosowski, Pathway’s CPO discusses Resilient Logistical Analytics.
The topic of the episode is closely related to Pathway’s expertise in studying real-world systems from a distributed computing perspective, specifically wondering how distributed systems can be used to understand the real world.
One of the major challenges in logistics is aggregating and making sense of data at scale, which is where machine learning analytics play a crucial role. Collecting data from the extreme edge - or in Disrupted, Disconnected, Intermittent, and Low-bandwidth (DDIL) environments,- such as containers in the middle of the ocean, presents challenges related to optimizing energy and communication for battery-powered IoT devices.
The use of Internet of Things (IoT) devices in the logistics and supply chain industry is discussed as a way to enhance end-to-end visibility and improve analytics capacity. However, challenges such as device stability, data accuracy, and timely data collection need to be addressed.
Pathway is then introduced as a framework to address the deficiencies in existing data streaming technologies. It provides advanced analytics pipelines on top of data streams and offers features that make it easier to handle IoT data, server performance monitoring, log monitoring, and more. The ability to use Python scripts for data streaming analytics in both real-time and batch modes is discussed, allowing data scientists and engineers to work in their usual development environments, while enabling faster decision-making and quicker response to customer needs in various industries such as logistics, transportation, or finance.
The podcast produced is also available on most platforms:
Apple Podcasts - Spotify - Soundcloud - Youtube.
IoT Data Analytics: Processing Real-World Data in Real Time
Pathway is Featured in Gartner’s Market Guide for Event Stream Processing