Google Cloud Platform

GCP is a very complicated platform, with unlimited potential for those who know how to use it; but once you learn how to use a specific tool - it becomes a very powerful and simple tool to use.

I currently only use the Compute Manager (Virtual Machine), VPC Network (External IP) and Network Services (Cloud DNS) to run a cloud-based Wordpress site. Overall, once you learn the system, Google Cloud offers a very powerful solution for web management - giving unlimited potential for upgrades & sizes, allowing for localized solutions & access to the full Google Cloud network, and giving a (cheap) solution for powerful web hosting. With GCP, we spend only $7 a month (CAD), and our site runs significantly faster than it previously did on other hosting services.

On top of that, GCP allows complete control over the backend linux server; which is a learning curve in itself, but offers quick & easy ways to manage every aspect of your website - the PHP version, specific file permissions, custom platform solutions (such as access to install different Google API's).

Google Cloud Platform is an insanely powerful platform with incredible features, but it also carries a VERY steep learning curve and is not for the faint of heart. While other web hosting services provide a simple interface most people can learn quickly, GCP throws you into the deep-end; requiring deeper knowledge of linux code (for backend management) and an understanding of web hosting in order to operate properly. Fortunately, with numerous guides and support forums/groups out there, it can be easy to learn.

The integration with other Google products is particularly impressive and makes it easy to set up. Using Forms for entry to Sheets which sync to BigQuery and DataStudio makes for very quick and easy expansion. Recently they have added a feature whereby query results can be viewed in Sheets for quick, less technical analysis.

I was particularly impressed by BigQuery's free public datasets: such as covid.

AppSheet is much easier to use than MS PowerApps.

They are continually adding novel features, with a natural language processing feature coming soon, allowing SQL queries to be composed using natural English.

BigQuery does not feel like a mature product yet. The UI can be buggy and is not particularly user friendly.

DataStudio lacks the flexibility of software like MS PowerBI; it lacks basic scientific graphs like boxplots and control charts and I would not recommend it for scientific data.

AppSheet lacks the flexibility of MS PowerApps and is priced per user, making it expensive to scale and greatly reducing the potential use cases.

+ Free tier available
+ Highly scalable
+ Security
+ Pay-as-you-go option ,so we have to pay only pay only for the usage.
+ Bring your own License capability.
+ Very easy to integrate with Google services.

+ Less number of datacenters across the world comparing to other vendors.
+ Pricing is bit complex
+ Customer services and support services could be improved

My marketing team uses Google Cloud Platform to collect Google Analytics clickstream data and marry it with structured data from other sources. I analyze that correlated dataset using SQL queries. Some benefits I see off using GCP: I can access data online using a Google email address which I already use for other Google tools. I can export the data extract using Google Sheets and store it in Google Drive. I can import additional data by setting up a daily feed from Google Analytics. So, I get the benefits of a relational database with ability to scale using Google servers.

Google Cloud Platform is great for importing datasets from Google Analytics and other Google suite tools. But from tools which are not in the Google eco system, it involves heavy lift from ETL developers or architects. Additionally, GCP Bigquery tool has a limit on the volume of queries an analyst can run. Once that limit or cap is crossed, companies have to pay extra. So, using the LIMIT command in SQL becomes critical to limit the numbers of rows. Also, there is a challenge of legacy SQL vs. current version because they use different syntax.