Redash LLM Chatbot: AI-powered Analytics & Insights Unlock the power of your Redash dashboards and databases with natural language queries and automated insights.

Transformative Redash add-on which integrates Flask, PostgreSQL, and OpenAI's GPT-3.5 Turbo for advanced data analytics with natural language processing and SQL translation. Empowering non-technical users to effortlessly fetch and visualize data using dynamic interactions and intelligent query generation.

This repository contains code that builds a DWH tech stack using PostgreSQL, DBT and Apache Airflow.

support es within redash

This repository implements a real-time sales data pipeline leveraging Apache Kafka, Apache Spark, Apache Cassandra, and Redash. It facilitates the efficient ingestion, processing, storage, and visualization of sales data streams.

Redash's query-runner for mixpanel

A data-warehouse built for the pNEUMA open dataset of naturalistic trajectories of half a million vehicles collected by a swarm of drones in a congested downtown area of Athens, Greece.

Export Redash Queries SQL and Dashboards as JSON

Sql Schedule & Python Schedule & Jupyter Schedule use redash rq schedule trigger

The aim of this project is to build a novel Redash chat add-on that we can use to extract insight from multiple Redash dashboards and from connected databases using natural language.

Aplicación para descargar, extraer, analizar y visualizar todos los datos sobre la evolución del COVID-19 en España

ELT pipeline with MySQL, Redash, Apache Airflow, dbt

Scalable data warehouse tech-stack

A city traffic department wants to collect traffic data using swarm UAVs (drones) from a number of locations in the city and use the data collected for improving traffic flow in the city and for a number of other undisclosed projects. Your startup is responsible for creating a scalable data warehouse that will host the vehicle trajectory data ex…

Data Engineering: Data warehouse tech stack with MySQL, DBT, Airflow, and Spark

Automated Python-based Report Generator which fetches CSV data from Redash queries, converts it to an XLSX or PDF report, and emails it using SendGrid.

Build an end to end data application with Yelp review dataset. (data collect -> DB config -> data ETL -> data dashboard (analysis/ML)