Sparklyr makes it easy and practical to analyze big data with Ryou can filter and aggregate Spark DataFrames to bring data into R for analysis and visualization and use R to orchestrate distributed machine learning in Spark using Spark ML and H2O SparkingWater. Edgar Ruiz walks you through these features and demonstrates how to use sparklyr to create R functions that access the full Spark API.

Tony Xing offers an overview of Microsoft's common anomaly detection platform, an API service built internally to provide product teams the flexibility to plug in any anomaly detection algorithms to fit their own signal types.

Recently, the volume of data collected from farmers' fields via sensors, rovers, drones, in-cabin technologies, and other sources has forced Monsanto to rethink its geospatial processing capabilities. Naghman Waheed and Martin Mendez-Costabel explain how Monsanto built a scalable geospatial platform using cloud and open source technologies.

Unbounded, out-of-order, global-scale data is now the norm. Even for the same computation, each use case entails its own balance between completeness, latency, and cost. Kenneth Knowles shows how Apache Beam gives you control over this balance in a unified programming model that is portable to any Beam runner, including Apache Spark, Apache Flink, and Google Cloud Dataflow.