{"repo":"DataKitchen/data-observability-installer","free":true,"listed":false,"github":"https://github.com/DataKitchen/data-observability-installer","clone":"git clone https://github.com/DataKitchen/data-observability-installer.git","description":"Installer for DataKitchen's Open Source Data Observability Products. Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end to end.","language":"Python","stars":141,"topics":["data","data-engineering","data-observability","data-profiling","data-quality","data-science","datacleaner","datacleaning","dataops","dataquality"],"license":"Apache-2.0","category":"data-pipelines","readme_excerpt":"DataKitchen Data Observability Installer Data breaks. Servers break. Your toolchain breaks. Ensure your data team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems from end to end. This repo contains the installer and quickstart setup for the DataKitchen Open Source Data Observability product suite. DataOps Data Quality TestGen is a data quality verification tool that does five main tasks: (1) data profiling, (2) new dataset screening and hygiene review, (3) algorithmic generation of data quality validation tests, (4) ongoing production testing of new data refreshes and (5) continuous periodic monitoring of datasets for anomalies. DataOps Observability monitors every tool used in the data journey, from source to customer value, across all environments, tools, teams, datasets, and databases, enabling immediate detection, localization, and understanding of problems. Interactive Product Tour Features What does DataKitchen's Open Source Data Observability do? It helps you understand and find data issues in new data . It constantly watches your data for data quality anomalies and alerts you of problems. It monitors multi-tool, multi-data set, multi-hop data analytic production processes. And it allows you to make fast, safe development changes . Prerequisites Minimum system requirements - 2 CPUs - 8 GB memory - 20 GB disk space Ins","default_branch":null,"files":null,"tree":[],"storefront":"/r/DataKitchen","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/DataKitchen/data-observability-installer/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}