Archive: 2018-01

Data analysis is complex and, at times, overwhelming. Automation increases an analysis team's ability to continuously improve their process. Specifically, the automation of software is the best way to manage all of the iteration and repetition that proper data analysis requires. DevOps is the perfect fit when planning a project that requires software, automation, and collaboration. In particular, DevOps improves all aspects of the data analysis process and allows teams to automate all software-based aspects of the data analysis process and effectively collaborate with all project stakeholders. In this blog post, I explore the ways in which DevOps improves data analysis.

When it comes to information technology services that are customer facing, traditional enterprise organizations tend to favor stability over change. According to a Netcraft survey from March of last year, there were 185 million web sites hosted by Windows 2003, an operating system that has been out of support since July 2015 . Many of these servers are still running because of the "if it isn't broken, don't fix it" motto. While reducing software and system churn would seem like the best way to promote stability, it can eventually harm application security and stability. This blog post explores some basic DevOps practices that will improve application security while helping to maintain a stable operating environment.