Financial Services, Media
Business Intelligence, Data Analytics, Data Warehousing
Client is a music funding platform that enables artists to access capital without giving up ownership of their music or control of their careers.
The data model and data points required to establish solutions were missing and an in-depth analysis of the existing platform with HubSpot was required to carry over the project.
As a first step, a model was created for the data, and data points were identified in HubSpot.
As a part of the solution, the existing API in python was modified, and a .csv was generated for all required data.
With the help of Airflow, an automated schedule was setup to push .csv file to an AWS S3 bucket.
The data was then transformed and stored in a snowflake data warehouse with proper definitions of facts and dimensions using the Galaxy schema.
Data marts were developed on top of the data as per access management for different roles and the department.
Using tableau, embedded analytics were created for various data sets as per requirements on customer life cycle, conversion, lag time, and many more.
Embedded analytics is well established with client software using tableau and batch processing of data mapped in Snowflake for analytics purposes using Airflow.
Analytics helped the client to reduce lag time by 2.89% and acquire more customers by 7.65%.
AWS-based infrastructure was setup using containerization with Kubernetes and Docker with continuous monitoring and fault tolerance setup in place, interacting with a Microsoft .net application for embedded analytics.