The easy-to-use open source Business Intelligence and Embedded Analytics tool that lets everyone work with data :bar_chart:

📊 Cube Core is open-source semantic layer for AI, BI and embedded analytics

Dashboards and notebooks in a single place. Create powerful and flexible dashboards using code, or build beautiful Notion-like notebooks and share them with your team.

Tabix.io UI

The modern replacement for Jupyter Notebooks

Based on my own experience, I believe this roadmap provides clear answers to all the key questions about becoming a data analyst from scratch, including which technologies and programming languages to learn, what soft skills are essential, and how to start a professional career in this field.

Abixen Platform is a microservices based software platform for building enterprise applications delivering functionalities through creating particular microservices and integrating by provided CMS.

Lightweight Open Source Business Intelligence and reporting tool for mongodb, postgresql, Mysql, MS sql, oracle, & google bigQuery allow users create their own reports just dragging and dropping, widestage also has a data governance layer AKA semantic layer

The analytical and reporting solution for MongoDB

Databao agent is an open-source agent that enables you to chat with your data and receive answers in text, interactive charts, and tables.

Databao Context Engine is an open-source engine that automatically generates a governed semantic context from your databases, BI tools, documents, and spreadsheets. It runs locally in your environment and integrates with any LLM to deliver accurate, context-aware answers

Set of queries designed to measure how users are consuming queries and dashboards.

Datu Core AI Analyst open-source

Archived - Please use fork below

Data Mart As A Service

The Awesome Panel CLI makes it super simple to develop high-quality data apps with Panel 💪

Dashboard Builder connected to Km4City smart city platform, developed per REPLICATE H2020

Build interactive big data apps with Altair and Vega easily using Panel + VegaFusion.

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This repository contains analysis of IMDB data from multiple sources and analysis of movies/cast/box office revenues, movie brands and franchises

Presentation Slide Decks & Demos

IONDV. Framework: Report module is to form the analytical reports.

In this project, I designed a Data Warehouse in Snowflake for business analysis of the dealership NovaDrive Motors. I used Apache Airflow to extract raw data from PostgreSQL and load it into the Staging layer of the DWH. Then, I transformed the raw data with DBT into insights to build the BI dashboard for sales analysis

Developed a business report on Microsoft Power BI for an electronics company with many hidden filters and slicers by currency, date, and location. Dedicated separate pages and used DAX to build KPI for Sales, Stores, Products, Customer, Profitability Analytics and Shipment Efficiency.

R Shiny business dashboard for an online grocery service. The dashboard provides descriptive statistics of sales & products as well as automated report & invoice generation.

Business Intelligence Course work - R Studio (Neural Networks, Deep Learning, Data Warehousing)

Business Intelligence Reports and Data dashboards on Tableau and PowerBI

A data analysis project aimed to understand the ping pong behaviour in the IT system of Volvo IT Belgium. The data is of the year 2013 as provided in the 2013 Business Process Intelligence Challenge. It uses python programming language on Jupyter notebook for ease.

Blinkit Sales Performance Power BI Dashboard A data-driven Power BI dashboard analyzing Blinkit’s sales, outlet performance, and customer spending trends using SQL, Power Query, and DAX. Built to demonstrate advanced data modeling, visualization, and business intelligence storytelling in retail analytics.

SETL is a data integration tool. It provides a unified platform for processing and integrating data semantically by bridging Semantic Web and BI technologies. SETL allows to create a semantic Multidimensional Data Warehouse (SDW), a repository of semantically integrated data by combining different data sources. We divide the whole integration process into three layers: Definition Layers (DL), ETL Layers (ETLL) and OLAP Layers (OL). The output of one layer is the input of the immediate next layer. In DL, user can define 1) the target with MD semantics using OWL, QB and QB4OLAP constructs and 2) the mappings between source and target. constructs. ETLL is composed of a set of operators which are used to create ETL flows to create a SDW. OL provides an interface where user can create their analytical query by selecting different levels of hierarchies and measures.