Christine Doig spoke at this year's OSCON Conference about data science as a team discipline and how to navigate the data science Python ecosystem. InfoQ spoke with Christine about challenges data science teams need to address to be more effective.
We review the book Infrastructure as Code by Kief Morris, who lays down the foundation for Infrastructure as Code and outlines the main patterns and practices recommended for building it.
Big Data Analytics with Spark, authored by Mohammed Guller, provides a practical guide for learning Apache Spark. InfoQ and the author discuss the book & development tools for big data applications.
In this fourth installment of Apache Spark article series, author Srini Penchikala discusses machine learning concept & Spark MLlib library for running predictive analytics using a sample application.
Olivier Bonsignour on what "X-Raying" software means, how it can help prevent software disasters and why CIOs should care. 3
Data Science has been getting lot of attention as organizations are starting to use data analytics to gain insights into their data. This article takes a closer look at Data Scientist role in 2016.
Current enterprise data architectures include NoSQL databases co-existing with RDBMS. In this article, author discusses a solution for managing NoSQL & relational data using unified data modeling. 5
Sourcing Security Superheroes: Part II: How Policy Can Enhance, Rather Than Hinder, Breach Detection
In theory, security policies protect organizations, stakeholders, and users. But in practice, organizations become more concerned with meeting these standards than protecting the business.
Our physical world is about to become digitally enabled and according to various predictions, there will be many billions of IoT devices going online and collecting data in the coming years. 1
In this article, third installment of Apache Spark series, author discusses Apache Spark Streaming framework for processing real-time streaming data using a log analytics sample application. 6
In this article, author discusses the survival prediction of colorectal cancer as a multi-class classification problem and how to solve that problem using the Apache Spark's MLlib Java API.