Privacy and Security focused Segment-alternative, in Golang and React

JavaScript SDK for RudderStack - the Customer Data Platform for Developers.

rtdl makes it easy to build and maintain a real-time data lake

Data analytics, exploration, sentiment analysis and topic analysis (LDA) on Amazon customer reviews. And cool interactive plots.

📋 Need more information about your merchants or customers on your marketplace site? Add new data fields to their profile pages for them to fill-up.

Containerized PostgreSQL client for executing SQL commands in containerized environments

Rust SDK for RudderStack - Open-source, warehouse-first Customer Data Pipeline and Segment-alternative. It collects and routes clickstream data and builds your customer data lake on your data warehouse.

Create an abstract component with a customer data to not duplicate the code to each component and send many requests to BE

Postman collection with example API calls for rtdl services

Repositories of analytics workshop

Fork of Analytics Next (aka Analytics.js 2.0) that enables carbon copying (cc-ing) an additional endpoint

Churn Modelling - unusual rate at which customers leaving the company, we need to figure out why? we need to understand the problem? We actually need to create a demographic segmentation model to tell the bank/company which customers are at high risk of leaving.

Project: Classifying consumers and minimising canvassing costs

This is a simple website instrumented with analytics-next-cc and made to run in an httpd container

Type-safety for the Gigya / SAP Customer Data Cloud REST API & Web SDK

We maintain all customers in one database. There are heaps of customers who have user cards. So, I decided to split up the customers based on the country and load them into corresponding country tables.

Generate Swedish test customer data!

The template repository for rtdl repositories

Analysis conducted using Excel and SQL to uncover metrics pertaining to Tantalizing Textile's Market Representation based on each unique customer's most recent purchase, resulting in insights being presented in Tableau

RNN and LSTM based text classification model on a dataset of customer complaints about consumer financial products.