“When it’s done well, it does look easy. People have no idea how complicated and difficult it really is. When you think of a movie, most people imagine a two-hour finished, polished product. But to get to that two-hour product, it can take hundreds or thousands of people many months Read more…
Introduction: In this blog, I will discuss the challenges my team faced while creating the process, and since the resources we had at hand were unable to answer our questions, we came up with our own approach to solve the issue. Since, ICRT uses XQuery, we used XQuery programming for Read more…
Simply put, Monkey Patching is the dynamic replacement of attributes at runtime. Monkey Patching can only be done in dynamic languages, of which Python is a good example. In Python, patching module (or class) variables or functions is simple, because Python doesn’t create protected or private entities– and in most Read more…
Apache Spark has a colossal importance in the Big Data field and unless one is living under a rock, every Big Data professional might have used Spark for data processing. Spark may sometimes appear to be a beast that’s difficult to tame, in terms of configuration and tuning queries. Mistakes Read more…
With the onset of the fourth industrial revolution, we see the end of conventional embedded systems in industrial usage. The Industrie 4.0 demands that systems be interconnected or networked in such a way, that they are easily upgradable and maintainable. Application deployment and updates on the conventional systems including proprietary Read more…
We all know that the mobile world is ruled by two giants – iOS and Android. However, it was very hard to maintain consistency, resource management, and time efficiency by developing separate applications for iOS and Android. So, developers began thinking about the possibilities of a cross-platform ecosystem. Today, there Read more…