People often ask me why Google Cloud specifically for Analytics & AI? By the way of this post, I am trying to answer why I choose Google Cloud to build Analytics & AI systems.
If you look at Analytics or Machine Learning, the core building block for Analytics & AI is Data. You can not build a Machine Learning system without having a ton of data and without having a platform that can process that amount of data.
Google’s mission is “to organize the world’s information and make it universally accessible and useful”. Google is a data company.
Data comes from the consumption of services. There are only 13 services in the world that have at least a Billion Monthly Active Users users.
Two of them are by Microsoft, i.e. Windows and Office; Two by Facebook, i.e. Facebook and Whatsapp; And nine of them by Google.
All of you are probably familiar with each one of them and use them on a daily basis.
Google is a unique company with 9 of these apps with more than Billion Monthly Active Users, many of them with more than two billion users. Just think about how much data these apps must be generating.
All of these services are free for you. This data is critical to monetization of these apps. These apps are highly data-intensive and are fully loaded with Machine Learning.
This means Google needs to build products and infrastructure that can process and analyze that amount of data.
Which means they have the capability, the infrastructure, engineers, and algorithms to be able to run Analytics & Machine Learning at that scale.
Google has built Machine Learning systems for close to 2 decades now. Because of the amount of data that Google generates and processes, it gives me confidence that there is no other company in the world that runs Analytics and Machine Learning at the scale that Google does.