Cloud Service Architecture for NLP in Google Cloud
This academic article was developed through my postgraduate course, DAT-03 Data Analysis in Big Data Environments, which presents a business case in which a company is interested in combining and migrating relational databases in Microsoft SQL Server and Oracle DB. Given the need to feed them with an NLP system output of social networks such as Instagram, Telegram, and Facebook Messenger.
Initially, the vulnerabilities that the company has when managing its data in a Local Storage are shown, where it is compared with the advantages of implementing a Cloud Service. This service is compared with others such as Microsoft Azure and Amazon Cloud Services, showing why this solution is the one that best suits the business case.
An architecture diagram was designed, covering the required APIs to the ingestion, storage, processing, and loading of the data in BI tools to ease access to the end-user.
Finally, financial aspects are covered in terms of operating costs for the proposed solution.
In case you want to access it, next you will find a link where it was uploaded to my LinkedIn. Click HERE to access or download.