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)
A comprehensive guide to building a modern data warehouse with SQL Server, including ETL processes, data modeling, and analytics.
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
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.
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.
Data modeling & the Snowflake Data Cloud using SqlDBM Hands-on lab - corresponding scripts.
Data Warehouse with AWS Redshift and Visualizing data using Power BI
Performed data pre-processing, optimized data warehousing, applied statistics and machine learning, and used Power BI for insightful visualizations to support informed decisions
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
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.
Data warehousing date dimension and time dimension builders written in Python.
Practical examples supporting Data Engine Thinking.
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