Predictive Maintenance (PdM) on IoT Data for Early Fault Detection w/ Delta Lake

Join us for an online tech talk on Delta Lake. Tech talks include a technical presentation with slides and a demo, with time for Q&A at the end.

Zoom link to join: https://databricks.zoom.us/j/661426529

Abstract:
Predictive Maintenance (PdM) is different from other routine or time-based maintenance approaches as it combines various sensor readings and sophisticated analytics on thousands of logged events in near real time and promises several fold improvements in cost savings because tasks are performed only when warranted. The top industries leading the IoT revolution include manufacturing, transportation, utilities, healthcare, consumer electronics & cars. The global market size for this is expected to grow at a CAGR of 28%. PdM plays a key role in Industry 4.0 to help corporations not only reduce unplanned downtimes, but also improve productivity and safety. The collaborative Data and Analytics platform from Databricks is a great technology fit to facilitate these use cases by providing a single unified platform to ingest the sensor data, perform the necessary transformations and exploration, run ML and generate valuable insights.

Agenda:
10:00AM - 10:45AM - Presentation + demo by Anindita & Denny
10:45AM - 11:00AM - Q&A

Speakers:
Anindita Mahapatra is a Solutions Architect at Databricks with over 5 years of experience architecting and delivering big data solutions. She has both product and Big Data Consulting experience working with clients across industry verticals helping them build analytic solutions to deliver timely business insights.

Denny Lee is a Staff Developer Advocate at Databricks. He is a hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale infrastructure, data platforms, and predictive analytics systems for both on-premise and cloud environments. His current technical focuses include Distributed Systems, Apache Spark, Deep Learning, Machine Learning, and Genomics.