Even if your business has virtually zero to do with technology, implementing a little tech-innovation into your business can work wonders by boosting your overall sales and making your customers happier.
Machine Learning as a Service (MLaaS) is a relatively new type of platform offered in the cloud. These are cloud services designed to help build, train, and then run predictive models incorporating machine learning (ML). ML can be handy for any organisation, whether it’s in accurately predicting sales data for the next month in a small business, through to a large enterprise building a custom chatbot for customer service.
What a time to be alive! When cars can (almost) drive themselves, our phones can unlock just by showing our face, and Siri can schedule meetings for us… Isn’t life grand? And easy? Machine Learning is seeping into our everyday lives - it’s not just operating behind the scenes in business helping banks spot fraudulent transactions, bolstering against enterprise cybersecurity attacks, and helping allocate and deallocate computing infrastructure for reduced operational costs.
Developing your own app is an important thing to get right, whether it’s for use within your own business, client-facing, or for the general public. One of the first decisions to make when developing an app is the choice whether to develop for the browser (web app), or for native use (downloaded to computer or mobile).
As a small business owner, you need your company to run like a well-oiled machine. One of the best ways to make sure your business is running as efficiently as possible is to implement custom software.
MVP isn’t just an acronym for Most Valuable Player. It’s also a term used often in the software world: Minimum Viable Product. What is an MVP? Well, in a nutshell, it’s the bare bones piece of software that fits its essential purpose. For example, for a music player app, a screen with a big fat play button that plays all the songs in your Music folder. It’s a starter software to the bigger picture!
Fixed price contracts can be rather tricky in a Scrum environment. Classic software development and Agile software development are very different from one another, and things that work in one environment don’t necessarily work in another.