How to Integrate Big Data into the Backend of Your Mobile AppNeeti Kotia
A full-featured, sophisticated mobile application these days can have as many as 100,000K lines of code, which should be considered a feat in itself, but the fact is, it?s not. It?s common, not enough. If you know anything about the tech world, you must have come across the term AI-first strategy that aims to make everything smart. In that respect, the massive amount of data that users share with applications is far more valuable than the code it is running on. From social media habits to shopping patterns, apps need not only make those tasks easier but also learn from them.
So how do you create such applications? Or to be more precise, how do top mobile app development services integrate such features into their apps? Well, the process is much simpler than most people realize. You don?t actually have to write those long, complicated algorithms by yourself but simply use them according to your needs. Here is how:
As users interact with your application, they generate a lot of data that only grows exponentially as the popularity of your app grows. To handle such massive amount of data is a challenging task, but thanks to the advent of cloud services, it can now be managed just by a few clicks.
Services like Azure, AWS, App Engine, among others, can store and maintain the integrity and security of your data at a fraction of the cost it would take to create such infrastructure on-premise. Though all of these clouds offer similar services, there are subtle differences that you must carefully evaluate before subscribing to one.
Mining big chunks of data for valuable information about customers isn?t a new thing but as these technologies become more accurate, cheaper, and widely accessible, their relevance has risen in the recent times. The data you store in the cloud is useless unless you are able to mine useful information from it, and thanks to the highly specialized and cutting-edge tools available, you won?t have to do it by yourself.
No matter which cloud service you used for data storage, there is a good chance that it would also offer analytic services. Depending on your business, you can use the data for many different kinds of analytics, each of which will reveal a different pattern.
For instance, if you have social media application, you can monitor the images any user shares and the corresponding response they get. This data, when analyzed for some time, can enable your application to offer customized suggestions before users share an image. From eCommerce to logistics to healthcare, this is one aspect where sky is the limit when it comes to inferring information from the available data sets.
It is not necessary that what works for one application would also work for you. After all, how can one decide if Netflix?s recommendation engine is better or Amazon?s? Both of them have their own approach towards the same problem and both are fairly successful. So, when it comes to knowing your customers and creating a custom experience, the only rigid rule is to stay flexible.
Many businesses still find these features and capabilities that only the top enterprises with deep pockets can deliver. The truth is just the opposite. All these tools are now easily accessible on a pay-as-you-go basis, which means you only have to pay for what you actually use. Furthermore, top app developers from India are renowned for delivering such cutting-edge features at very reasonable costs.