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Enabling Scalable Data Analytics with Elastic - Justin Kambic

Data analytics is a broad and ever-changing topic. The tools used to ingest, store, index, and analyze data are more imperative to business success now than ever before, and our reliance on them continues to grow over time. In this talk, I will introduce the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash) and explain how millions of users leverage it to collect and store raw data, and refine those data into actionable information. I’ll conclude by touching on our commercial Machine Learning product, and show how it can be used to analyze arbitrary data, identify patterns, and create alerts or informed recommendations for future decisions.

You’ll see how hundreds of organizations as wide-ranging as GoDaddy, Yelp, Uber, Tinder, and the Wikimedia Foundation use these tools to drive a variety of business initiatives. By the end of this talk you will hopefully have a better understanding of Elastic’s technology, and perhaps even have a cool use case of your own in mind!

Bio
Justin is a UI Developer on the Ingest team at Elastic. His primary contributions include UI and backend features for Logstash monitoring and centralized management, and upcoming features for Beats centralized management. In his spare time Justin is an incessant tinkerer, and loves to make use of Elastic’s products in novel and interesting ways.

Scalable and robust data processing on Kafka/Samza stack - Akim Akimov

In the modern world, businesses often experience the need to process vast amounts of data with only the result of the processing being relevant. Many times, the data itself isn't even required to be stored, and as an additional challenge, there can be unexpected varieties of loads. Creating a resilient infrastructure can really be a challenge under these conditions. To achieve these goals, Akim will present on architecture ideas to realize such a system on AWS which will have you ready to start processing your data within hours.

Bio

With a background in engineering data pipelines, quantitative science and a personal passion for math, Akim helps create the infrastructure to move, store and process data that HealthVerity receives from its partners. With a deep understanding of systems architecture and an ability to solve complex problems, Akim oversees the data processing and ensures its accuracy and efficiency.