Think you developed a secure mobile app? Think again. Many mobile app developers have a naive notion of app security that leads them into believing their apps are secure when they are not. Some developers authenticate users and encrypt passwords and think that they’re all set, but there could still be security holes so wide you could sail a ship through them. The results of releasing an insecure app can include financial loss, reputation tarnish, lawsuits, and Twitter shame.
When designing your mobile apps and mobile backend services, be sure to consider the six security properties of confidentiality, integrity, availability, authentication, authorization, and nonrepudiation (see Figure below). Simply considering how each security property applies to your app won't make it more secure. You will need to perform threat modeling on your design and find solutions to secure your app based on your specific technology and use cases. Don't forget that the mobile backend services must be secure too.
I love predictive analytics. I mean, who wouldn't want to develop an application that could help you make smart business decisions, sell more stuff, make customers happy, and avert disasters. Predictive analytics can do all that, but it is not easy. In fact, it can range from being impossible to hard depending on:
Causative data. The lifeblood of predictive analytics is data. Data can come from internal systems such as customer transactions or manufacturing defect data. It is often appropriate to include data from external sources such as industry market data, social networks, or statistics. Contrary to popular technology beliefs, it does not always need to be big data. It is far more important that the data contain variables that can be used to predict an effect. Having said that, the more data you have, the better chance you have of finding cause and effect. Big data no guarantee of success.