Postgres read replica optimized for analytics

Qbeast-spark: DataSource enabling multi-dimensional indexing and efficient data sampling. Big Data, free from the unnecessary!

A curated list of open source tools used in analytics platforms and data engineering ecosystem

Sample Data Lakehouse deployed in Docker containers using Apache Iceberg, Minio, Trino and a Hive Metastore. Can be used for local testing.

DatAasee - A Metadata-Lake for Libraries

My M.Sc. dissertation: Modern Data Platform using DataOps, Kubernetes, and Cloud-Native ecosystem to build a resilient Big Data platform based on Data Lakehouse architecture which is the base for Machine Learning (MLOps) and Artificial Intelligence (AIOps).

This repository is a place for the Data Warehousing course at the Information Systems & Analytics department, Santa Clara University.

The project aims to process Formula 1 racing data, create an automated data pipeline, and make the data available for presentation and analysis purposes.

Data lakehouse at home with docker compose

This project implements an end-to-end techstack for a data platform, for local development.

Инфраструктура для data engineer S3

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

STEDI project

Всё что нужно знать про DuckDB

This is an example project how to build a serverless data lakehouse on AWS using Terraform, Apache Iceberg and Spark.

#Test - Create a Data Lakehouse in Kubernetes

Qbeast-spark: DataSource enabling multi-dimensional indexing and efficient data sampling. Big Data, free from the unnecessary!

Canalización desde MongoDB hacia un Data Lake de Amazon S3, creación de Data Warehouse en Amazon Redshift y visualización en Tableau.

This project is aimed at overhauling a university's data infrastructure to improve efficiency, security, and scalability, resulting in the successful creation of a unified data management solution.