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5 Steps to Implementing a Data Literacy-Driven DataOps Framework
DataOps is a new framework that has been gathering greater attention in the past year since it first appeared on the Gartner Hype Cycle. DataOps is defined as a new way of thinking related to data which encompasses people, processes, and technology, resulting in improved collaboration and streamlined decision-making... Read more
Why Do Businesses Need a Data (and AI) Manifesto?
50 years ago, the concept of privacy meant disappearing. You built a wall around your private data, and it was pretty easy to keep that wall secure. Aside from governmental intrusion, you didn’t have to worry much about constant feeds of data streaming from your daily activities into the... Read more
5 Mistakes You’re Making With DataOps
Data is the driver for just about every modern business, and as companies consume more data more intelligently, there’s a need for a better community and higher buy-in. DataOps stands to do to data what DevOps did to development.   [Related Article: Data Ops: Running ML Models in Production... Read more
7 Steps to Go From Data Science to Data Ops
Not too long ago, data operation wasn’t on the radar, but now that it’s all people talk about, how can you move efficiently from data science to data ops? Gil Benghiat, co-founder of Data Kitchen, shares seven steps to do just that. [Related Article: The Difference Between Data Scientists... Read more
Data Ops: Running ML Models in Production the Right Way
Editor’s note: Check out Ido’s talk at ODSC East 2019 this May, “From Zero to Airflow: Bootstrapping Into a Best-in-Class Risk Analytics Platform.” The tipping point Many organizations reach the point in which new goals for SLA, scale, or efficiency simply exceed the capabilities of their existing data / ML... Read more