northsurge.com USED TECHNOLOGY
Svelte
Figma
Neo4j
SQL
Python
BRIEF DESCRIPTION
Established in 2017, in Ribeira Grande, North Surge is a surf and skate shop that offers a large variety of brands and aims to deviate from the ordinary looks of apparel stores. Most of their furniture and decorations are handcrafted, in order to achieve a traditional and woody yet clean apeparence.
I tried to take this design philosophy into the digital world, taking assets and inspiration from the physical place, and keeping it minimal at the same time, both regarding the amount of information presented to the user and in the navigation of the website itself.
FEATURE HIGHLIGHT
Features present in this project that I personaly was very satisfyed with.
BACKOFFICE MANAGEMENT PLATFORM
A platform to manage the database items with some abstraction was created, mainly in order to insert new items, manage stocks, analyse statistics and create and manage sales.
SEMI-AUTOMATIC DATABASE SYNCRONIZER
This company had their own database from their billing software. Since it wouldn't be safe to simply expose said database nor it was the intention of the owner to display all items available in said database online, I created a program that reads and adapts data to be recognized by the online database. Features include bulk updates of stock (sales and returns) and bulk insertion of new items based on supplier invoices.
PRODUCT BOOKMARKS
Using a simple local cookie, a presistent product bookmark functionality was created.
FINAL THOUGHTS
Definently my most dense project so far. Maybe the toughest part of this journey was in the pre-developing stage, where I was trying to find a neat yet simple solution to meet all the logistics demands of the project, like the database syncronization and finding the best way to organize product information in the graph database. Despite all uncertainties and challenges, as this project was comming together, things got progressively clearer and previous doubts about my approach were slowly turning into solid foundations.
I decided to switch from the ol' reliable SQL database to a Graph one due to the fact that I felt it would be more intuitive to fetch some groups of items like by brand, category, etc. As every product would have a lot of assossiated values (for example, brand, size, color or category), i felt like the SQL joins would eventualy end up in a mess, and Graph databases provide another level of (at least visual) organization in this regard.