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June 17, 2019 – DataOps is an emerging set of practices, processes, and technologies for building and automating data pipelines to meet business needs quickly. It speeds cycle times while reducing defects.
December 19, 2018 – This article presents a framework for understanding DataOps processes, technologies, and data flows.
June 30, 2018 – This report will examine the role of DataOps in BI, analytics, and data management.
October 31, 2019 – This report drills into the technology and tools required to build robust, automated data pipelines with DataOps.
July 4, 2019 – Converging development and operations for data pipelines and analytic modeling is the essence of DataOps.
DataOps uses automated testing, orchestration, collaborative development, containerization, and monitoring to continuously accelerate output and improve data quality. It builds upon the software engineering principals espoused in DevOps, but in a manner more specifically tailored for data. How do you get started on obtaining these benefits? We explore how in our "shop talk" webinar.
July 9, 2019 – DataOps helps data engineers and scientists get machine learning right. Improve results with modular development, flexible execution and rigorous testing.
December 30, 2019 – Self-driving data has become a reality. Just like autonomous vehicles automate driving, self-driving data automates data using DataOps techniques.
November 1, 2018 – In this episode, Wayne Eckerson and Shakeeb Akhter dive into DataOps. They discuss what DataOps is, the goals and principles of DataOps, and reasons to...
November 11, 2020 – This article examines the emerging role of the DataOps engineer, a dedicated technical staff member responsible for the data development lifecycle.
December 1, 2020 – DataOps is a new practice that is gaining adoption as organizations recognize the importance of transitioning from artisanal to industrial-scale processes for developing and running data pipelines. DataOps enables organizations to evolve from slow, one-off development efforts to a team-based development approach that can build, change, and manage thousands of pipelines with high speed and accuracy.
May 6, 2020 – Design patterns have proven valuable in many endeavors. Can data pipeline design patterns help to break the data engineering logjam?
April 1, 2018 – Data engineering is one of the hottest and most difficult jobs to fill in the field of analytics. Breadth and depth of required skills limits the number...
August 28, 2019 – This report surveys data and analytics professionals and provides an overview of the trends in DataOps, including adoption rates, benefits, challenges,...
September 6, 2019 – Learn how to achieve the DataOps objectives of improved efficiency and data quality by migrating to a streaming architecture based on Apache Kafka.
