A platform that connects mentors and coachees using machine learning and data analytics.
Our customer is a European e-learning platform that provides customers with mentors on the subjects of their choice.
Detailed information about the client cannot be disclosed under the provisions of the NDA.
A client came up with the idea that the platform should be enhanced with data engineering and machine learning tools so that it could suggest mentors to users more rapidly and accurately. Data should be properly gathered and refined before being used by recommender systems, time-logging tools, and other software.
To solve the problem, Innowise Group’s software engineers needed to
Our software engineers have designed the solution in a way that allows data to be rapidly gathered and updated from various sources. The data is automatically refined according to the preset templates and sent to the tools that operate it.
Amazon Web Services
The solution is based on Amazon Web Services due to its security, flexibility, scalability, and cost-effectiveness.
Coaches and regular customers can submit their data in various forms to the platform, including text, pictures, videos, document scans, etc. This data is uploaded to AWS and stored in a data lake.
Our data engineers have developed and introduced ETL pipelines to automatically gather data chunks from the users into the cloud storage.
Data lake and data warehouse
Data gathered through ETL pipelines is refined in data lakes. This process is operated by Airbyte and dbt. After the data is refined, Apache Airflow transfers it to the data warehouse where it can be used for various purposes, such as
Taking into consideration all the project requirements and specifics, we have selected Scrum as a software development methodology, conducting bi-weekly sprints and Sprint overviews to demonstrate the progress. We used Jira and Confluence and held the meetings and overall communication with the client in Microsoft Teams.
Our team developed the requirements according to the client’s vision of the solution and documented them. During the development process, we were constantly analyzing, refining, and decomposing the requirements into tasks and subtasks for easier progress tracking. After several tasks were completed, Innowise Group’s quality assurance engineers checked whether the solution was compliant with the outlined requirements, was bug-free, and our team was on the same page with the client’s vision and expected outcomes.
Innowise Group has built a secure platform that allows the client’s employees to collect, store, and manage data from students and tutors on the platform. Due to the security of the solution and strict access and operation control, this information can be used for a variety of purposes without fear of being leaked.
Our software engineers have automated a number of processes that were previously manual and designed the data flow to make the solution as efficient as possible.
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After examining requirements, our analysts and developers devise a project proposal with the scope of works, team size, time, and cost estimates.
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