Shaunak Kashyap looks at several well-understood concepts and SQL queries from the relational paradigm and maps these to their Elasticsearch equivalents.
Nuri Halperin discusses the aggregation framework in MongoDB, explaining the pipeline architecture, major operators, and how to put it all together in interesting and effective ways.
Lawrence Chernin describes best practices and validation methods used to deal with large unstructured data, including a suite of unit tests covering the implementations of algorithmic equations.
Alan Barrington-Hughes and Pavithra Ramaswamy discuss key concepts in agile database refactoring, demonstrating a no outage deployment with nginx using a blue-green method.
Beach Clark talks about the technological and cultural challenges of turning data science into a vital part of the business model at Georgia Aquarium.
Alok Aggarwal overviews Artificial Intelligence and discusses a use case, “Voice of Cancer Patients” that uses ML and NLP algorithms to analyze unstructured text written by cancer patients.
The panelists discuss how Data Science can help solve various problems for business.
Songxiao Zhang introduces Pyh3, a graph visualization library showing tree nodes in a 3D hyperbolic space.
Lenley Hensarling describes how EnterpriseDB Cloud Management can provide responsible DevOps models for the enterprise.
Jonathan Gray introduces Hydrator, an open source framework and user interface for creating data lakes for building and managing data pipelines on Spark, MapReduce, Spark Streaming and Tigon.
Ali Jalali presents how to develop a machine learning predictive analytics engine for big data analytics.