DataOps is a philosophy whereby the various stages of development, from analysis to design to development to testing and maintenance, are increasingly integrated through software or machine-learning based systems. Articles in this section focus on both DataOps as a philosophy and business practice, as well as explore deeper technical aspects that make DataOps feasible.
What is a Feature Store? Machine learning is such a new field that a mature industry-wide standard practice of operations has not yet emerged, like… Read More »Why the Feature Store Architecture is so Impactful for ML Teams
Learn how StreamSets, a modern data integration platform for DataOps, can help expedite operations at some of the most crucial stages of Machine Learning Lifecycle and… Read More »Model Experiments, Tracking and Registration using MLflow on Databricks
The digital transformation is driving organizations to modernize their legacy systems and apps. With the pace of change in the tech industry, modern organizations are… Read More »Transform Legacy Apps to Microservices using the DevOps Approach
Introduction Andrew Ng is a key reference point for me in understanding AI. Andrew Ng is always easy to understand especially for new… Read More »Model-centric to Data-centric AI – Am I Missing Something?
The efforts to find means and solutions to enable safe and quick development of software have led us to the doorstep of DevSecOps. But what… Read More »DevSecOps: Top Best Practices
Have you heard IDC’s latest predictions on DevOps? According to this study, the DevOps market expects to grow from $2.9 billion to $8 billion by… Read More »DevOps Trends 2021: DevOps Enters a New Decade with the Hottest Trends
Have you heard IDC’s latest predictions on DevOps? According to this study, the DevOps market expects to grow from $2.9 billion to $8 billion by… Read More »DevOps Trends 2021: DevOps Enters a New Decade with the Hottest Trends
MLOps, AIOps, DataOps, ModelOps, and even DLOps. Are these buzzwords hitting your newsfeed? Yes or no, it is high time to get tuned for the… Read More »MLOps: Comprehensive Beginner's Guide
Data is more present and more powerful than ever. It can be tapped to tailor products, services and experiences. It contains insights on all manner… Read More »DataOps: Building an Efficient Data Ecosystem
Welcome to the first installment in our series on ModelOps. This blog focuses on the importance of Data Gathering and Preparation in support of your… Read More »Maximizing Data Use and Reducing Pitfalls: Putting the Right Data Preparation Process in Place for AI
