https://keen.io/ JavaScript SDKs. Track users and visualise the results. Demo http://keen.github.io/keen-dataviz.js/

💳 ETL (Extract, Transform and Load) pipeline for calculating stats for a transactions database & testing the efficacy of a loyalty program. 💻

This repository contains the Business Intelligence insights generated as part of the final project challenge for the DTU Data Science course 42578: Advanced Business Analytics

In the retail industry a trade area, also known as a catchment area, is the geographic area from where you draw your customers. Here I derive trade area from scratch

Have you ever wondered who your most valuable customers are? This project, created for a software company, sought to identify those who stand out above the rest.

Trained a model that estimates if a lead is likely to be converted based on lead behavior in historical customer data using ML.

A Data Analysis project performing Exploratory Data Analysis (EDA) on Global Electronics' data to uncover insights that enhance customer satisfaction, optimize operations, and drive business growth.

A short hand-picked collection of resources to help SaaS founders get started with customer interviews.

This program helps to create sales reports based on warehouse sales data

Key: descriptive statistics and exploratory data analysis, forecasting (linear regressions, ARMIA, Prophet), and a Tableau dashboard that delivers customer insights such as RFM analysis.

This repository contains a list of open source and comercial platforms that take insights from user and chatbot models conversations

Workshop for integrating Dynamics 365 Customer Insights and Azure Data Services

📊 Sales Data Analysis – Coffee Shop | Analyzing sales trends, payment methods, and top-selling drinks using Python (Pandas, Matplotlib, Seaborn).

This project provides an interactive analysis of Superstore sales data using Tableau, offering insights into sales performance, customer behavior, and market trends to help optimize business strategies.

This project demonstrates customer segmentation using K-Means clustering, a popular machine learning technique. By analyzing customer data, we group customers into distinct segments to better understand their behaviors and preferences. This segmentation can help businesses tailor their marketing strategies and improve customer satisfaction.

Behavior-based consumer segmentation and predictive modeling using R for AXANTEUS client analysis.

A Node.js-powered tool that scrapes high-quality SaaS product reviews from platforms like G2, Capterra, and Trustpilot (Bonus). Scrapeflow — structures Reviews into clean, standardized JSON—empowering product teams to extract insights, monitor sentiment, and prioritize what matters most.

This repository features the Retail sales and customer insights dashboard demonstrating data cleaning and analysis using Excel, Python, and SQL, along with interactive visualization in Power BI. Explore the code and reports to gain insights into sales performance, customer behavior, and product trends. A complete end-to-end data analytics workflow

This capstone Power BI analytics project was developed to support Techtronix Innovations, a leading AI player in the microchip and robotics industry. The project addresses key business challenges including sales strategy optimization, customer insights, inventory management inefficiencies, and identification of profitable market opportunities.

"A comprehensive SQL-based analysis of a banking database for 'The Big Bank'. This project explores customer banking behavior, transaction trends, and account management. The analysis aims to optimize banking operations, enhance fraud detection, improve customer segmentation, and increase revenue using data-driven insights."