The client’s company is an innovative consulting firm working towards providing quality education for millions around the world by creating social impact through educational marketing solutions.
2 years of cooperation | EdTech
Tools Used:
Python | Django | Rest API | Postgres | SQL | AWS | ML | AI | DBT | Metabase
Challenges:
The project deal was on education data and one of the major problems our client was facing is data mapping and data collection. There was a huge collection of data but no uniformity. There were also no similarity scores for the districts.
Each book was under a different district which was a huge challenge for the client. A huge number of jpg files also needed to be removed. And a lack of understanding from our client’s perspective to get the data right.
Solution:
To comply with the client’s requirements our team started working efficiently on data mapping and web scrapping. Our team used tools like Django, SQL, ML, and AWS for proper structuring in the following ways:
- Our team performed web scrapping on all social media platforms like LinkedIn, Facebook, Twitter, and other portals. And the data that we collected from there included un-uniformed logos. Which we uniformed through machine learning for more visual and clean data.
- There was a requirement to get similar districts with the same curriculum, features, student count & school count. To achieve this our team used the Euclidean Distance Algorithm method for effective results.
- Each product was of a different name & district and the client requirement was to get everything in one for which it needed to be mapped together. And to achieve this we accessed data from google books and APIs and there was a huge success in the results.
Results:
The end product was a success and well received by Gates Foundation. Our client was happy with the outcome and it will be available to the public soon.
