Time management has been engrained in our brains since we were young. Even when we were in grade school, we had specific times every day when we completed certain tasks, whether it be reading time, math time, lunchtime, or even nap time. Well now it’s a little different, but still essentially the same. Even though we may not have nap time every day (though I’m sure many people wished we did!), we still have certain tasks that need to be completed every day.

There has never been more pressure on development teams to build software faster and more efficiently. The rise in popularity of DevOps has largely been the result of its promise to speed up dev cycles, increase agility, and help teams resolve issues more quickly. And while the availability and sophistication of DevOps tools have improved greatly in the last few years, simply choosing the latest and greatest tools is no guarantee of a smooth, problem-free development lifecycle.

The principles of Agile project management took root in the software development and engineering fields. There are many different methodologies (such as Scrum or Kanban) on how to implement these processes, but agile does not have to be complicated and can be applied to any field (but maybe shouldn’t be). This article aims to take you a few steps beyond the simple principles of Agile, with actionable information, while avoiding the dogma of any particular methodology.

When it comes to switching to a new programming language, timing is of the essence in order to land qualified programmers for the project. The language must be new enough to bring technical progress, and at the same time tested and disseminated in such a way that there are enough qualified programmers who will enjoy working with it.

Artificial Intelligence refers to the simulation of human intelligence processes by machines, computer systems to be precise. These processes primarily include learning, reasoning, and self-correction. Machine learning is a term that is synonymous with AI. As the name suggests, machine learning refers to empowering machines to learn by themselves using the data provided and predict the best possible outcome of a complex problem.

Human Resources Learn what it takes to keep employees engaged and content from these pioneering company leaders

How do you like the idea of creating an application that will be rebranded by others? Your client gets to resell it as their own product, but not before they pay you all the charges for production/designing. If this idea interests you, then this page is where you need to be. Take a break from your work or anything that you’re doing right now. This blog post needs your undivided attention. 5 minutes will be enough. Let’s start with the basics.

The new year is here and with it comes our annual list of key customer service trends! Our 2019 trends article was a huge hit, so here’s what is set to make an impact in 2020…

In OneDesk, dashboards are a type of ‘view’ which are displayed in the left panel and show you some useful charts and statistics about your data. You can create and save your own dashboard-views, just like you can create tree-views, card-views, gantt-views, etc.

Unless you build or program computers for a living, you could be forgiven for never having wondered what actually happens under the hood. How do computers make decisions? What do their instructions look like? Can they, y’know… think?