Data analytics play a central role in the healthcare system by improving outcomes and quality of life while helping to control costs. In this article, author describes the role analytics can play with the emerging wearable technologies with biophysical interfaces, physiological sensors, and embedded diagnostic tools.
In this article, author Carlos Bueno describes a method for analyzing constraints on the shape and flow of data in systems. He talks about the factors useful for system analysis like working set & average transaction sizes, request & update rates, consistency, locality, computation, and latency. He also discusses big data architecture details of two use cases, movie streaming and face recognition.
The book "R for Everyone: Advanced Analytics and Graphics" authored by Jared P. Lander covers the R programming language and how to use it for data analytics and visualizations. InfoQ spoke with Jared about the R programming language, book, and big data analytics and visualization.
Apache Spark is an open source big data framework built around speed, ease of use, and sophisticated analytics. In this article, Srini Penchikala discusses how Spark helps with big data processing. 3
Datameer, a big data analytics application for Hadoop, introduced Datameer 5.0 with Smart Execution to enhance the data analytics. InfoQ spoke with Matt Schumpert from Datameer about the new product.
"Analytics Across the Enterprise" book is a collection of experiences by analytics practitioners in IBM. InfoQ spoke with authors about lessons learned and IBM technologies in the Big Data area.
Cindy Walker spoke at Enterprise Data World Conference about using semantic approaches to augment data management practices. InfoQ spoke with her about these best practices and data analytics.
Lambda Architecture proposes a simpler, elegant paradigm designed to process large amounts of data. In this article, author discusses Lambda Architecture with the help of a sample Java application. 20
How do you bringing agility into big data? Learn what makes analytics uniquely different than application development, and how to adapt agile principles and practices to the nuances of analytics.