Why The Mobile World Is The Future Of Data Management And Acquisition

If you’re a technology enthusiast, chances that you’ve stumbled across the usage of data are pretty high, especially in the past couple of years. Big data, in particular, has become quite a considerable topic within technology, mainly due to what happened last year with the Cambridge Analytica scandal. With this being said, it’s quite easy to understand how big data and data, in general, have been part of the mobile world recently. Let’s analyse what the future of data on mobile is all about.

Neural Networks and Constant Connection

I know, these two may sound like two overcomplicated concepts but, in all reality, they are not. With neural networks, we intend architectures which are made, programmed and finalized to constantly deliver and process big data on what users are looking for. The power of neural networks highly applies to mobile as a whole, given the fact that mobile devices are connected to the internet 24/7 (in 80% of the cases). With this being said, and by combining pieces of technology like voice search to specific digital marketing strategies, it’s quite easy to state the power of data-oriented architectures, especially on mobile.

From a Coding Perspective

The power of machine learning applies to mobile as well. There are tons of libraries available, currently, but the one which many app developers like to use is definitely tensorflow.js. Tensorflow, for those who are coding experienced, is a machine learning library which is made to automate tasks based on data. With this in mind, there are, easily, a lot of different marketing applications for this very matter: imagine having a fully automated application which constantly gathers data (prior to the user’s confirmation) and then uses it to target internal ads, or simply optimise specific location-based features.

The Usage Of Data Lakes On Mobile

Data lakes have become quite an impactful element within data science as a topic and their usage on mobile to process complex and bulky influxes of data has been something highly looked after by many companies with big AWS architectures, for example. The usage of data lakes on mobile may seem like overkill but, in reality, there are several applications which are already using data lakes-based architectures to both gather and process constant small influxes on data via mobile. Apple was the first (of course after AWS) to implement a small data lake architecture with iOS 10. The usage of data lake architectures is very likely to become an industry-standard in regards to mobile app development.

The Market Value

When it comes to analysing a piece of technology, it’s mandatory, especially if relatively experimental, to analyse its market value. What better way to analyse the market value of a specific piece of technology than evaluating its investment routes and the amount which was actually given to startups? Data-oriented technologies have conquered more than 35% of Swift development project in the first half of 2019, peaking at 40% in August. Data lake as a whole is, as of today, the most looked after architectural piece of technology in the US and Europe, with companies like Amazon (which, keep in mind, owns the entire AWS protocol), Apple and Google. Currently, data applications on mobile are surpassing the billion dollars value.

Is The Future Of Data Management, Then, Mobile?

It is indeed, the usage of data-friendly architectures will very likely set the foundation, also, for a new operating system which, instead of relying on manually inputted data, will be based around automatically gathered and processed data (whether if big or physical). We can safely expect companies like Apple and Google to update their native operating mobile systems with the usage of data lake infrastructures. With this in mind, it’s mandatory to state the fact that this technology will reach a level of “industry standard” not before 2030, when processors of the current generation will be used on mobile devices.

To Conclude

The usage of data lake architectures is extremely complex to implement, especially on mobile but, when done correctly, it could lead to a massive optimisation in terms of both processing and delivery, in particular on big architectures like the ones Amazon and Apple currently have. With this being said, according to Forbes and to the data mentioned above, we can safely say that data lake-oriented architecture will be the future of mobile as a whole, starting from 2020. The future is, now more than ever, data friendly and data oriented.