Machine learning has been the biggest technology trend in the past couple of years. Its usage impacted sectors like finance, warehouse management, general development and, of course, data. In the recent past, app development as a whole has embraced a lot of new pieces of technology, whether if from a purely architectural point of view or from a front-end related one. Machine learning and the usage of data lakes and AWS-based features have become two of the most prolific topics within app development in 2019, let’s analyse why.
Why Data Lakes?
A data lake is a structure which operates locally on via cloud and that gathers and processes data for printing features. This may sound complicated but in reality, especially when applied to mobile as a whole, its entire processing is pretty straight forward: the fact that mobile devices are generally connected to the internet 24/7 creates a big potential in regards to the usage of these architectures, which are, indeed constantly processing data for marketing purposes.
Can This Be Considered The Second Machine Learning Revolution?
What’s The Future?
Many app developers have stated how the usage of machine learning and data science-oriented features has helped them in building and creating fast performing apps which automatically process issues and other forms of minor dysfunctions without relying on a developer. Automation within troubleshooting and time management is a mandatory aspect of development within the machine learning industry and it’s very likely to grow further in the nearest future.
App development and machine learning are a match made in heaven. With all the new technologies which are being connected to the mainstream at the minute, we can safely say that, from 2020, there will be many, many more Python developers in app development agencies and big enterprises like Amazon, Twitter and Facebook.