Session: 2 for 1: Elasticsearch Essentials: Data Loading with Python for Interplanetary Insights / Open Source Privacy-Preserving Metrics
Jessica Garson: Elasticsearch Essentials: Data Loading with Python for Interplanetary Insights
Ever wanted to stay up to date with the latest Asteroid news? Discover the techniques for importing your data into Elasticsearch with Python. This talk will explore how to efficiently transfer data from a Pandas DataFrame into Elasticsearch, maintain an up-to-date index through the use of Google Cloud Platform’s Cloud Functions and Cloud Scheduler, and leverage the power of parallel bulk operations. The dataset that will be used for this talk will be Near Earth Object Web Service (NeoWs), a RESTful web service that provides near-earth Asteroid information.
Sarah Gran & Brandon Pitman: Open Source Privacy-Preserving Metrics
Telemetry and metrics collection can provide an enormous amount of useful information about applications and their users. From time-on-site to tracking software versions in crash reports, metrics enable informed engineering and business decisions. This type of information can also be used to feed AI and ML Large Language Models. But all that data sitting around can also be a liability when it can be pieced together to develop an increasingly robust understanding of an individual user. In today’s world that is rife with data thievery and data-driven bias, it’s time to explore how to have your cake and eat it too when it comes to metrics collection. We’ll introduce you to set of novel privacy-preserving metrics collection protocols that are being developed in the IETF and deployed in Open Source repos at Divvi Up.
