#typescript #business_intelligence #data_analytics #data_visualization #dbt

https://github.com/lightdash/lightdash

#rust #apache_arrow #computer_vision #data_analysis #data_analytics #data_centric #data_format #data_science #dataops #deep_learning #duckdb #embeddings #machine_learning #mlops #python

https://github.com/eto-ai/lance

#typescript #analytics #apache #apache_superset #asf #bi #business_analytics #business_intelligence #data_analysis #data_analytics #data_engineering #data_science #data_visualization #data_viz #flask #python #react #sql_editor #superset

Superset is a powerful business intelligence tool that helps you explore and visualize data easily. It offers a no-code interface for building charts, a robust SQL Editor for advanced queries, and support for nearly any SQL database or data engine. You can create beautiful visualizations, define custom dimensions and metrics quickly, and use a lightweight caching layer to reduce database load. Superset also provides extensible security roles and authentication options, an API for customization, and a cloud-native architecture designed for scale. This makes it easier to analyze and present your data in a user-friendly way, replacing or augmenting proprietary BI tools effectively.

https://github.com/apache/superset

#python #ai #cv #data_analytics #data_wrangling #embeddings #llm #llm_eval #machine_learning #mlops #multimodal

DataChain is a powerful tool for managing and processing large amounts of data, especially useful for artificial intelligence tasks. It helps you organize unstructured data from various sources like cloud storage or local files into structured datasets. You can process this data efficiently using Python, without needing SQL or Spark, and even use local AI models or APIs to enrich your data. Key benefits include parallel processing, out-of-memory computing, and optimized vector searches, making it faster and more efficient. Additionally, DataChain integrates well with popular libraries like PyTorch and TensorFlow, allowing you to easily export data for further analysis or training models. This makes it easier to handle complex data tasks and improves your overall workflow.

https://github.com/iterative/datachain