datawarehousing

A comprehensive guide to building a modern data warehouse with SQL Server, including ETL processes, data modeling, and analytics.

A free to use dbt package for creating and loading Data Vault 2.0 compliant Data Warehouses (powered by dbt, an open source data engineering tool, registered trademark of dbt Labs)

Working with relational data models in R

Mapping of DWH database tables to business entities, attributes & metrics in Python, with automatic creation of flattened tables

implementing an end-to-end tweets ETL/Analysis pipeline.

Data Engineering, Data Warehouse, Data Mart, Cloud Data, AWS, SAS, Redshift, S3

A REST interface for Mondrian ROLAP server

Building Json data pipeline within Snowflake using Streams and Tasks

Scripts complement the Optimizing a Data Vault data warehouse on the Snowflake Cloud Data Platform webinar

Data Analysis, Analytics, Science, AI & ML, LLM etc.

This repo provides a step-by-step approach to building a modern data warehouse using PostgreSQL. It covers the ETL (Extract, Transform, Load) process, data modeling, exploratory data analysis (EDA), and advanced data analysis techniques.

This project demonstrates the creation of a Data Warehouse using SQL Server 2022. It includes the design of dimension and fact tables, ETL processes for data integration, Python scripts for synthetic data generation, and SQL queries for KPI analysis to support business decision-making.

Genomic BigData Warehousing with Apache Spark and LakeHouse Architecture

Explore the transformative power of data analytics in my portfolio, where Google Analytics and Snowflake converge to provide comprehensive insights. This project leverages advanced ETL techniques and real-time data integration to enhance user engagement and optimize content delivery effectively.

Performed data pre-processing, optimized data warehousing, applied statistics and machine learning, and used Power BI for insightful visualizations to support informed decisions

Data modeling & the Snowflake Data Cloud using SqlDBM Hands-on lab - corresponding scripts.

Practical examples supporting Data Engine Thinking.

Data Warehouse with AWS Redshift and Visualizing data using Power BI

A data warehouse and business intelligence project on Stock market dataset to answer non-trivial BI queries.

Efficient YouTube data harvesting and warehousing with Python, SQL, MongoDB, and Streamlit, enabling seamless analysis and visualization for insightful decision-making in content management and audience engagement strategies