In 1998, Netscape decided to release their source code in an effort to attract new users to their product and new developers who could easily integrate applications with the browser. At the same time, there seemed to be a groundswell around a culture of open and collaborative development, with legacy software companies beginning to acknowledge Linux and open source software (OSS) as a legitimate option for enterprise solutions.
2018 is the year of the cloud, and as more and more companies move to cloud technologies it is important to realize how your business can best utilize the cloud. One of the biggest issues enterprises are having today, is moving their data from their on-premise databases to their cloud data storage. This can be a long, and tedious process if you don’t have the correct tools. Luckily, Talend is here to help!
It’s an exciting time to be working in the Cloud, Big Data, and Machine Learning industry, but it’s even more exciting to hear how Talend customers are building their data strategy to drive business results. Every year we invite representatives from some of our most strategic customers to join us for two days to share their experiences with Talend’s products and provide input into our roadmap.
Cloud computing in the form we understand today started around 10 years ago, with the launch of Amazon Web Services (AWS). This was the first commercially viable option for businesses to store data in the cloud rather than on-premise and acted as a shared service for anyone connecting to the platform.
The 35 million people who saw Skyfall back in 2012 were in for a treat – thrills, tension, and a spectacular hacking attempt against the UK public sector. While many have picked up on the evident flaws in the Bond version of MI6’s approach to cybersecurity, the film provokes an interesting reminder that in our rush to digitize public services, there is certainly more to be done in ensuring that these services are secure.
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.
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.
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.
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.
DevOps is a set of practices that automates the processes between software development and IT teams so they can build, test, and release software more quickly and reliably. The concept of DevOps is founded on building a culture of collaboration between IT and business teams, which have historically functioned in relative siloes. The promised benefits include increased trust, faster software releases, and the ability to solve critical issues quickly.
