DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. While DataOps began as a set of best practices, it has now matured to become a new and independent approach to data analytics. DataOps applies to the entire data lifecycle from data preparation to reporting, and recognizes the interconnected nature of the data analytics team and information technology operations.
Data Engineering notes in Vietnamese
gliff.ai SUPPORT – a user documentation for the gliff.ai platform: user-friendly interface for curating, annotation and collaborating with imaging dataset for the purposes for machine learning development.
DataOps Architecture and Central Data Repository for a modern Fintech product
Automated weather data pipeline demonstrating CI/CD, Docker, GitHub Actions and DataOps principles.
Source-available AIOS snapshot for personal, non-commercial learning only · 仅限个人非商业学习
Pipeline ETL automatizado (DataOps) que extrae, procesa y visualiza ofertas de empleo tecnológico en Chile usando Node.js, Python, PostgreSQL y Streamlit.