Skip to content

Made by Don’t Stop Beerlieving

Review your brew!

All team members came up with an idea and we narrowed it down to a winner following a vote. The winner was Brew Review which is an app that allows users to view information about beers and breweries, to post reviews on existing beers in the Brew Review database, and to add beers that they try to the database. It also allows beer newbies and enthusiasts to connect with each other and share their beer interests.

The Team

Manuel Gonzalez

Manuel Gonzalez

An aspiring Software Developer who enjoys problem solving,

chess, and tennis!

GitHub LinkedIn
George Harper

George Harper

A python enthusiast (and he isn’t talking about the

snakes), a hobbyist video game creator, and is looking to become a Software Developer who has expertise in Java Script.

GitHub LinkedIn
Morgan Hewitt

Morgan Hewitt

Inspired by the use of technology to make a positive impact

(hence the beer related app of course). Enjoys climbing, tennis and piano.

GitHub LinkedIn
Nicole Raymond

Nicole Raymond

An aspiring Software Developer from London who is switching

careers from Advertising and Marketing.

GitHub LinkedIn
Katherin Bennett

Katherin Bennett

Curious, driven, and adaptable professional with a global

mindset and a passion for continuous learning.

GitHub LinkedIn
Sam Joy

Sam Joy

An aspiring Front End Developer who enjoys Football, and

loves Manchester United.

GitHub LinkedIn

Tech Stack

Tech Stack for this group

We used Firebase, Expo, React Native, NativeWind, Java Script, Figma, Jira, GitHub / Git, React Native Components, Android Studio Firebase – to gain experience in a no SQL database and to have the opportunity to use authentication. Expo – for the emulation and routing capabilities. React Native – to gain experience in a popular framework which allowed mobile development. Native Wind – to allow us to use Tailwind CSS within react native. Java Script – it is the language we have the most experience with collectively and it is easily compatible with react native. Figma – this was used to brainstorm ideas, and then create wire frames and a component tree, as well as to plan our app generally. Jira – used for project management, creating tickets and keeping track of our progress and what needs to be done. GitHub / Git – used for version control, and applying a rule set to manage pull requests within the team. React Native Components – toast, drop downs etc Android Studio – for emulation.

Challenges Faced

Merge conflicts – working in a group and managing how to deal with lots of separate pull requests but we overcame this by creating a rule set of 2 approvals per pull request and learning Git more deeply to understand it better. Spiking Technologies – learning new technologies and implementing them very quickly took some getting used to but we have all learned invaluably from that process. Android Studio – this took a heavy toll on some of our devices and emulation proved complicated but we found ways around this using Expo and XCode for those of us with Mac OS. Compatibility issues – across different operating systems, web, and mobile.

Brew Review

Made by Don’t Stop Beerlieving Review your brew! All team members came up with an idea and we narrowed it down to a winner following a vote. The winner was Brew Review which is an app that allows users to view information about beers and breweries, to post reviews on existing beers in the Brew…

Read More

Wedgwood

Made by Team Wedgwood Pipelines, not pottery! We created an Extract, Transform and Load data pipeline to practise our skills. This was based on the provided totesys database and designed to ensure data integrity, cost-efficiency, and ease of access for business intelligence purposes. The Team Arman Mestari With a strong foundation in data engineering and…

Read More

Trent

Made by Team Trent We move data so you don’t have to! Data Engineering showcasing an ETL Process. The project used CI/CD processes and agile methodology. The Team Annette Alcasabas Annette really likes coding in Python and although this was… a challenging project, she liked the whole experience! Eashin Matubber A passionate and results-driven Software…

Read More

Duck

Made by Team Duck Quacking the code, one pipeline at a time Terrific Totes – Cloud-Based Data Pipeline The Team Monika Kaploniak I am an engineer with two years of professional experience… in software development, having transitioned from a successful career in finance. I’ve always been drawn to the dynamic and problem-solving nature of tech,…

Read More

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…

Read More

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…

Read More

Splash World

Made by Team Splash World Driven by data. Powered by teamwork. We were approached by our client, Terrific Totes, a tote bag retailer, to build a data pipeline that extracts, transforms, and loads (ETL) sales data from their OLTP database (“Totesys”) into an OLAP data warehouse. The aim was to make their sales data more…

Read More

Spitfire

Made by Team Spitfire A Data Engineering project The aim of the project was to apply key skills picked up during the Northcoders bootcamp, to real-world, business requirements. We were tasked with helping a fictional company to create a platform for managing their enterprise data. We implemented a pipeline to move and transform data from…

Read More

Southport Pier

Made by Team Southport Pier It’s more than a bag, it’s a feature! This is an end-to-end ETL pipeline for a tote bag business. It pulls data from their database into a data warehouse for future analysis. In this projet, three lambda applications were created using psycopg2 and boto3. They were deployed in the AWS…

Read More

Royal Blue

Made by Royal Birkdale ain’t no birkdale, we blue The purpose of this repository is to build an entire ETL (Extract, Load, Transform) data pipeline in AWS (Amazon Web Services). Extracting data from an OLTP (Online Transaction Processing Database) PostgreSQL database and loading it into an OLAP (Online Analytical Processing Database) database. The data is…

Read More

Pottery

Made by Team Pottery Team Pottery: Crafting Code, Firing Up Success! Our Terrific Totes Project utilised an ETL pipeline orchestrated by a Step Function triggered every 30 minutes . Our Extract Lambda Handler connects to the Totesys database, checking for new data. Any new data found is then added to our S3 ingestion bucket as…

Read More

Oatcake

Made by Team Oatcake Putting ‘oat’ in tote! Implemented and deployed an automated ETL pipeline, integrated with AWS, for a simulated global tote bag business. The Team Beth Suffield I have a background in Digital Marketing and SEO, and… particularly enjoyed the technical side of these roles. I am especially motivated by the exciting advancements…

Read More