It’s plain for all to see that nearly everything is becoming increasingly data driven these days, and the explosive emergence of the IoT has fuelled a lot of that. Every effort made to harness data and either implement it or make decisions based on it is in the interests of competitive advantages, and for as long as we live in a capitalist society where only certain birds get worms that’s going to be the driving force behind much of what goes on in the digital world. Visualizations, analytics, and the ‘biggie’ – machine learning – are among other aspects of big data that are demanding more attention and more budgetary investment allowances that ever before. Machine learning in particular is kind of like an unexplored continent and it 1620 rather than 2020. Most of you who’ll be reading this blog won’t need us to go into the how’s and why’s of that, so we’ll just continue with where we’re going with all of this in today’s blog. Here at 4GoodHosting, it probably goes without saying that we’re very front and center in as far as the audience for all these developments are concerned. While anything regarding big data isn’t immediately relevant for us, it certainly is in a roundabout way and that’s very likely true for any good Canadian web hosting provider in Canada. The changes has been revolutionary and continue to be so, and so let’s get to today’s topic. While we are not shot callers or developers, we know that some of you are and as such here are 3 solid tips for applying agile to data science and data ops. All About Agile Methodologies Nowadays you’ll be hard pressed to find even one organization that isn’t trying to become more data-driven. The aim of course is to leverage data visualizations, analytics, and machine learning for advantages over competitors. Strong data ops programs are essential for providing actionable insights through analytics requires and the same goes for a proactive data governance program to address data quality, privacy, policies, and security. The 3 components and their realities that should be shaping aligned stakeholder priorities are delivery of data ops,...
