In this fourth installment of Apache Spark article series, author Srini Penchikala discusses machine learning concepts and Spark MLlib library for running predictive analytics using a sample application.
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. 2
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. 7
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.
This article summarizes the key takeaways and highlights from QCon San Francisco 2015 as blogged and tweeted by QCon's 1,300 attendees.
Data Lake-as-a-Service provides big data processing in the cloud for business outcomes in a cost effective way. InfoQ spoke with Lovan Chetty & Hannah Smalltree from Cazena about these solutions work.
In this article, author discusses a bio-informatic software as a service (SaaS) product which was built as a public data warehousing and analytical platform for mass spectrometry data. 3
Find out what's new in Kubernetes V1 with a Jenkins example in Google Container Engine. V1 brings enterprise-level capabilities such as self healing, service discovery, dynamic DNS, resource quotas.
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