Systems | Development | Analytics | API | Testing

February 2018

The Paradise Papers: How the Cloud Helped Expose the Hidden Wealth of the Global Elite

In early 2016, the International Consortium of Investigative Journalists (ICIJ) published the Panama Papers –one of the biggest tax-related data leaks in recent history involving 2.6 Terabytes (TBs) of information. It exposed the widespread use of offshore tax havens and shell companies by thousands of wealthy individuals and political officials, including the British and Icelandic Prime Ministers.

How to Structure Your Business to Make Better Use of Data

A few years ago, Starbucks’ director of analytics and business intelligence, Joe LaCugna, said the Seattle coffee giant once struggled to make sense of the data pouring in from its loyalty card holders, which at the time was over 13 million and comprise 36 percent of all Starbucks’ transactions.

Legacy Versus Next-Generation - How Open Source is Driving the Big Data Market

When it comes to solutions for the big data sector, there is a clear split between the legacy and next-generation approaches to software development. Legacy vendors in this space generally have their own large internal development organizations, dedicated to building proprietary, bespoke software. It’s an approach that has worked well over the years.

Talend Step-by-Step: Continuous Data Matching & Machine Learning with Microsoft Azure

Today, almost everyone has big data, machine learning and cloud at the top of their IT “to-do” list. The importance of these technologies can’t be overemphasized as all three are opening up innovation, uncovering opportunities and optimizing businesses. Machine learning isn’t a brand new concept, simple machine learning algorithms actually date back to the 1950s, though today it’s subject to large-scale data sets and applications.