In this post, we will run though a case study to setup an email deliverability analytics pipeline using SendGrid and AWS Big Data Services such as S3, Glue and Athena. To start off, when we send mails from SendGrid to recipients. we get responses (multiple response types are possible such as processed, delivered, blocked, deferred... » read more
A common use case in Machine Learning life cycle is to have access to the latest training data so as to prevent model deterioration. A lot of times data scientists find it cumbersome to manually export data from data sources such as relational databases or NoSQL data stores or even distributed data. This necessitates automating... » read more
Our focus in this post is to leverage Google Cloud Platform’s Big Data Services to build an end to end Data Engineering pipeline for streaming processes. So what is Data Engineering?Data Engineering is associated with data specifically around data delivery, storage and processing. The main goal is to provide a reliable infrastructure for data which... » read more