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How DataOps Kitchens Enable Version Control
This blog builds on earlier posts that defined Kitchens and showed how they map to technical environments. We’ve also discussed how toolchains are segmented to support multiple kitchens. DataOps automates the source code integration, release, and deployment workflows...
How to Build a Successful Cloud DataOps Program
We discuss the core capabilities required for a successful DataOps program and how a DataOps platform complements the tools provided by cloud vendors, ensuring that you get the most out of your cloud investment.
Eckerson Group: DataOps Deep Dive
Leading a DataOps Cultural Revolution Eckerson Group Best Practices in DataOps: How to Create Robust, Automated Data Pipelines DataOps promises to take the pain out of managing data for reporting and analytics. In most companies, data travels a tortuous route from...
Six Top DataOps Trends for 2021
Since the term was coined, DataOps has expanded the way that people think about data analytics teams and their potential. 2020 was a huge year in DataOps industry acceptance. Media mentions of DataOps are on track to increase 52% over the prior year. To date in 2020,...
Why DevOps Tools Fail at DataOps
Implementing DataOps requires a combination of new methods and automation that augment an enterprise’s existing toolchain. The fastest and most effective way to realize the benefits of DataOps is to adopt an off-the-shelf DataOps Platform. Some organizations try to...
Believe It Or Not, Your Tools are DataOps Compatible
Almost every data analytic tool can be used in DataOps, but some don’t enable the full breadth of DataOps benefits. DataOps views data-analytics pipelines like a manufacturing process that can be represented by directed acyclic graphs. Each node in the graph...
What is a DataOps Kitchen?
In a previous blog, we talked about aligning technical environments to facilitate the migration of analytics from development to production. In this post, we will introduce the concept of “Kitchens” and illustrate how they simplify the deployment of data analytics. In...
Environments Power DataOps Innovation
Production engineers and analytics developers sometimes row the enterprise boat in different directions. Perhaps it is their roles and objectives which keep them at odds. It’s the production engineer’s duties to keep data operations up and running. Innovation is good,...
A Tool-Agnostic Approach to DataOps Using the DataKitchen Platform
DataOps improves your ability to orchestrate your data pipelines, automate testing and monitoring, and speed new feature deployment. DataOps recognizes that, in any data project, many different tools play an important role as independent components of the data...
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A Guide to the Six Types of Data Quality DashboardsNovember 27, 2024
