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Case Study: Selecting Big Data and Data Science Technologies at a large Financial Organisation

Adopting Big Data and Data Science technologies into an organisation is a transformative project similar to an agile transformation and with many similar challenges. In this article, the author describes such a project for a FTSE100 financial services company.

Christian Prokopp
on Nov 10, 2016
AI, ML & Data Engineering

Solving Business Problems with Data Science

Enterprises are increasingly realising that many of their most pressing business problems could be tackled with the application of a little data science. This article, the first in a series, looks at the foundations of a successful business-orientated data science project.

Francine Bennett
on Nov 06, 2016
Java

Testing RxJava

You are ready to explore reactive opportunities in your code but you are wondering how to test out the reactive idiom in your codebase. In this article Java Champion Andres Almiray provides techniques and tools for testing RxJava.

Andres Almiray
on Oct 18, 2016
AI, ML & Data Engineering

Peter Cnudde on How Yahoo Uses Hadoop, Deep Learning and Big Data Platform

Yahoo uses Hadoop for different use cases in big data & machine learning areas. They also use deep learning techniques in their products like Flickr. InfoQ spoke with Peter Cnudde on how Yahoo leverages big data platform technologies.

Srini Penchikala
on Oct 13, 2016
AI, ML & Data Engineering

A Quick Primer on Isolation Levels and Dirty Reads

Recently MongoDB found itself at the top of Reddit again when developer David Glasser learned the hard way that MongoDB performs dirty reads by default. In this article we will explain what isolation levels and dirty reads are and how they are implemented in popular databases.

Jonathan Allen
on Oct 07, 2016
AI, ML & Data Engineering

Traffic Data Monitoring Using IoT, Kafka and Spark Streaming

Internet of Things (IoT) is an emerging disruptive technology and becoming an increasing topic of interest. One of the areas of IoT application is the connected vehicles. In this article we'll use Apache Spark and Kafka technologies to analyse and process IoT connected vehicle's data and send the processed data to real time traffic monitoring dashboard.

Amit Baghel
on Sep 28, 2016
Java

RXJava by Example

In the ongoing evolution of paradigms for simplifying concurrency under load, the most promising addition is reactive programming, a specification that provides tools for handling asynchronous streams of data and for managing flow-control, making it easier to reason about overall program design. In this article we overcome the learning curve with a gentle progression of examples.

Victor Grazi
on Sep 27, 2016
AI, ML & Data Engineering

Big Data Processing with Apache Spark - Part 5: Spark ML Data Pipelines

With support for Machine Learning data pipelines, Apache Spark framework is a great choice for building a unified use case that combines ETL, batch analytics, streaming data analysis, and machine learning. In this fifth installment of Apache Spark article series, author Srini Penchikala discusses Spark ML package and how to use it to create and manage machine learning data pipelines.

Srini Penchikala
on Sep 24, 2016
AI, ML & Data Engineering

The InfoQ Podcast: Cathy O'Neil on Pernicious Machine Learning Algorithms and How to Audit Them

In this week's podcast InfoQ’s editor-in-chief Charles Humble talks to Data Scientist Cathy O’Neil. Topics discussed include her book “Weapons of Math Destruction,” predictive policing models, the teacher value added model, approaches to auditing algorithms and whether government regulation of the field is needed.

Charles Humble
on Sep 16, 2016
AI, ML & Data Engineering

Spark GraphX in Action Book Review and Interview

“Spark GraphX in Action” book from Manning Publications, authored by Michael Malak and Robin East, provides a tutorial based coverage of Spark GraphX, the graph data processing library from Apache Spark framework. InfoQ spoke with authors about the book and Spark GraphX library as well as overall Spark framework and what's coming up in the area of graph data processing and analytics.

Srini Penchikala
on Sep 12, 2016
AI, ML & Data Engineering

Book Review: Cathy O’Neil’s Weapons of Math Destruction

“Big Data has plenty of evangelists, but I’m not one of them,” writes Cathy O’Neil, a blogger (mathsbabe.org) and former quantitative analyst at the hedge fund DE Shaw who became sufficiently disillusioned with her hedge fund modelling that she joined the Occupy movement.

Charles Humble
on Sep 06, 2016
AI, ML & Data Engineering

Chris Fregly on the PANCAKE STACK Workshop and Data Pipelines

InfoQ Interviews Chris Fregly, organizer for the 4000+ member Advanced Spark and TensorFlow Meetup about the PANCAKE STACK workshop, Spark and building data pipelines for a machine learning pipeline

Dylan Raithel
on Aug 29, 2016

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