Open Source Vs. Proprietary DataOps
Core DataOps concepts are making their way into data engineering teams and, from there, into the broader enterprise. Data engineers are retooling how they create data products, and much of this work revolves around creating data pipelines. DataOps pipelines offer the kind of observability that traditional data integration and ETL processes don’t or can’t. They […]
DevOps’ Data Storage Problem
The technology sector has always been about problem-solving. When the value of big data was finally embraced, thanks to new analysis capabilities developed in the late nineties and early aughts, the industry adapted its mindset toward storage by investing in on-premises data centers to help store the data that would drive better business decisions. When […]
Consider DataOps for a Competitive Edge
DataOps seeks to eliminate existing barriers between people, technology, tools and data It’s no secret that COVID-19 has put the economy under enormous strain and future economic prospects are uncertain. A smart way to give your organization a leg up against competitors is DataOps. Adopting a DataOps culture makes the best use of your data—it […]
The Taxonomy of DataOps
Data Operations, or DataOps for short, is one of those IT buzzwords that lots of people use, yet few can define precisely. Like the cloud or DevOps, DataOps doesn’t make sense until you sit down and really think through what it entails. To that end, let’s take a look in this article at the taxonomy […]
DataOps: DevOps Plus Big Data
In traditional DevOps, there are the complimentary forms of development operations (that I call DEVops), and development operations (that I like to call devOPS). Between them they automate the toolchain and bring the people working on getting an application out to users onto the same team—not necessarily the same organizational team, but using their strengths […]