The Usage Of Data Lakes In Mobile Could Change The World Of App Development

As many of you may know, technology as a whole (yes, the entire sector) has been heavily relying on building tools, software and everything in between with data-related features. Whether if it’s related to the acquisition, processing or anything else, data is the most valuable asset on earth and, therefore, companies and devs are highly looking into how it could improve their products/workflow. Let’s analyse why data lakes, specifically, could reshape the world of app development, the most competitive dev-related sector of 2019.

Why Big Data? And Why Mobile? 

Big data is extremely important for marketing purposes. By processing specific data with next level Python architectures, it’s easy to create ad-hoc campaigns which are presented to the right user at the right time. Big data and mobile are two natural born partners: being able to constantly acquire data from iOS or Android devices (prior to the user’s consent) to then process it is something which many app developers are investing time and effort to implement.

What Is A Data Lake? 

Per definition, a data lake is an architecture, whether if in the cloud or not, which gathers, stores and processes big data and other forms of data generated from file analysis. With this in mind, it’s quite easy to understand why, in case this is applied to mobile, this type of architectures is cloud-based. Data lakes require the processing power of 4 GHz currently to run at low specs mode, which is the reason why big companies like Amazon with AWS have been building complex cloud architectures.

How Can This Change The Future Of App Development?

As mentioned above, being able to constantly gather, process and use data which is acquired via mobile devices is something extremely powerful and competitive in a market which is trying hard to implement data-driven strategies. In regards to the actual development process, it will be a matter of understanding whether if Python developers will be able to apply their knowledge to Object C and Swift-based applications. Python, being a rendering-based programming language, requires processing power which sometimes is too elevated for these applications, therefore, this is still a purely theoretical matter.


What do you think?


Written by Ifan Faris

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