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DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with dataengineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?
Dave Farley – Pioneer of ContinuousDelivery & Author of the books “ContinuousDelivery” and “Modern Software Engineer”. Russ Miles – Chaos Engineer Thought Leader & Author of multiple books including “Antifragile Software: Building Adaptable Software with Microservices”.
Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Microservices Architecture and Design , July 8-9. Practical Linux Command Line for DataEngineers and Analysts , July 22. Domain-driven design and event-driven microservices , July 23-24.
Data science and data tools. Practical Linux Command Line for DataEngineers and Analysts , March 13. Data Modelling with Qlik Sense , March 19-20. Foundational Data Science with R , March 26-27. What You Need to Know About Data Science , April 1. Microservice Fundamentals , April 15.
Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Microservices Architecture and Design , July 8-9. Practical Linux Command Line for DataEngineers and Analysts , July 22. Domain-driven design and event-driven microservices , July 23-24.
Data science and data tools. Practical Linux Command Line for DataEngineers and Analysts , May 20. First Steps in Data Analysis , May 20. Data Analysis Paradigms in the Tidyverse , May 30. Data Visualization with Matplotlib and Seaborn , June 4. Microservices Caching Strategies , June 17.
Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together dataengineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.
This might mean a complete transition to cloud-based services and infrastructure or isolating an IT or business domain in a microservice, like data backups or auth, and establishing proof-of-concept. Either way, it’s a step that forces teams to deal with new data, network problems, and potential latency.
This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.
As 2020 is coming to an end, we created this article listing some of the best posts published this year. This collection was hand-picked by nine InfoQ Editors recommending the greatest posts in their domain. It's a great piece to make sure you don't miss out on some of the InfoQ's best content.
For several years, microservices has been one of the most popular topics in software architecture, and this year is no exception. Although DDD has been around for a long time, it came into prominence with the rise of microservices as a way to think about partitioning an application into independent services. growth over 2021.
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