customer-360

Deterministic identity-resolution engine in TypeScript: Zod-validated handlers, mocked deps, and a CLI that mirrors the future HTTP API.

Build the engagement layer once: one Microsoft Foundry agent in Teams acts across Salesforce, ServiceNow and your other systems of record, always as the signed-in user. Open-source reference implementation (APIM identity propagation, MCP meta-tools, azd).

End-to-end Customer 360 analytics platform with SQL, Python, ML, SHAP, and Streamlit for customer segmentation, churn risk prediction, health scoring, and revenue action planning.

Entify is an early open-source workspace for entity resolution, record linkage, and data deduplication. It helps teams profile messy datasets, configure Splink-powered matching workflows, and review explainable match clusters.

Customer 360 Data Engineering Pipeline on GCP using BigQuery, Dataform, and Looker Studio.

End-to-end banking data engineering project using Python, SQLite, SQL, PySpark, and Dagster. Includes ETL pipelines, data validation, relational modelling, incremental loading, analytics, medallion architecture, and a Customer 360 data product with a read-only HTTP API.

Customer 360 churn demo on Microsoft Fabric - behaviour-derived churn, Lakehouse + Direct Lake semantic model + ontology/graph + dual-source Data Agent. Fully config-driven and idempotent.

Integration patterns for Salesforce Data Cloud and SFMC to activate near-real-time customer journeys.

Customer 360 MVP with Python, PostgreSQL, Salesforce CRM, and Salesforce Data Cloud Identity Resolution.

A governed AI-powered Customer 360 data product demonstrating data engineering, RAG, agentic AI, enterprise architecture and governance-by-design.

Comprehensive Retail Analytics project containing the full data lineage (Bronze/Silver/Gold CSVs), SQL transformation scripts, and Customer 360 reporting logic.

Reproducible health-insurance Member 360 lakehouse with identity resolution, governed serving, hybrid retrieval, and grounded AI.

Customer 360° Banking Analytics platform for customer insights, product opportunity scoring, and Next Best Product recommendations using Python, Power BI, and data analytics.

An end-to-end Customer Behavior (Customer 360) Analysis built with Python, merging 9 datasets to uncover insights on revenue concentration, marketing performance, and customer risk.

Sync customer intelligence from a warehouse like Snowflake into operational customer profiles, compute rule-based segment membership, and activate (push) those profiles to downstream targets — all from one consistent, idempotent pipeline keyed on customer_key.

End-to-end Customer 360 and revenue analytics project using SQL, Python, Power BI, DAX, forecasting, cohort/RFM analysis, experimentation and marketing analytics on GA4 e-commerce data.

Production-ready Customer 360 Analytics Lakehouse built with Apache Spark, Delta Lake, MinIO, DuckDB, dbt, Docker, and Power BI.

Customer intelligence and Reverse ETL platform that turns Mandera commerce data into segmentation, Customer 360, and holiday-aware campaign recommendations, syncing insights into Monday CRM.

ETL pipeline unifying CRM and ERP extracts into a Customer 360 — declarative data-quality checks with quarantine, identity resolution, Pentaho design mapping Topics: etl, data-pipeline, data-quality, pentaho, identity-resolution, customer-360, python, sqlite

Headless sales-intelligence platform: one typed API over Snowflake, Postgres and S3, with a React + PatternFly front end