Systems | Development | Analytics | API | Testing

It’s that time of year - back to school, back to books, and our annual must-read books for data and analytics leaders. Given the pace of change in our industry, continuous learning is a must, whether through networking, podcasting, or reading. To cull this year’s list, I focused mainly on books published in the last two years with the themes of data, analytics and AI. I scoured lists and reviews on Amazon, solicited ideas from social networks and got to reading.

In government agencies around the world, large enterprise legacy systems are what stand in the way of desperately needed modernization programs. Such legacy systems can be large enterprise resource planning (ERP) implementations or custom-built applications using complex codebases. Simply put, they are not supportable, upgradable, and do not provide the rich user experience customers have become accustomed to.

How can you ensure data quality and security across your data analytics pipeline? With data governance – the exercising of authority and control over your data assets. It includes tracking, maintaining and protecting data at every stage of the lifecycle.

In our last post, we began comparing the PHP frameworks Laravel and Symfony. We went over an overview of each framework, and also what particular advantages each one has. In this post, we’ll continue by discussing the following: Finally, we’ll go over which framework is right for your particular use case.

It’s quite natural to become sidetracked when balancing the many activities involved in software development. You must keep track of deadlines, application goals and your piece of the project, while handling internal and external communications and producing good code. That’s where software development tools come into play. There are a variety of applications available that are designed to make tasks easier for a developer.