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Stoke

Made by Team Stoke

Stoke usage has been trending downwards

The project was a chance for us to showcase the skills and knowledge we have learnt over the last couple of months during our bootcamp, we did this by creating an Extract, transform, load pipeline, for the minimum viable product of the project specification. we collectively created a kanban board, breaking down the steps into tickets for each part of the project, followed by daily standups so the entire group understood what each other was working on, allowing us to work together and adapt as different people moved on to other tasks. utilising our understanding of python, terraform, amazon web services and git to create each step within the pipeline allowing us to take data from a prepared source, which was an Online Transaction processing database, to an Online Analytical processing database where would could make some visualisations of the data

The Team

Abdulmomen Jameli

Abdulmomen Jameli

Result-driven professional transitioning into data

engineering.

Amar Gandecha

Amar Gandecha

Very new to the world of coding and data engineering, was

eager and ambitious to dive into things head first and take on new challenges as they provided him with new experience allowing him to level up.

Duncan Cornish

Duncan Cornish

Data Engineer that is good at learning new technologies,

and applying them in fun and creative ways.

Mukund Pandit

Mukund Pandit

A career changer looking for an entry-level job as a data

engineer after the disappearance of my role in publishing. I find the prospect of working in technology exciting.

Neil Hallard

Neil Hallard

Quiet and curious.

Tech Stack

Tech Stack for this group

We used Github, Python, Terraform, AWS (S3, Lambda, Cloudwatch), postgreSQL, Tableau It matched the specifications and its technologies we had built up understanding and familiarity with over the course of the last 2 months.

Challenges Faced

Yes, there were multiple challenged all the way through the project, varying from small to large. Most were related to AWS not quite updating the code we had written as we thought it would.