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Believe It Or Not, Your Tools are DataOps Compatible

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?

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...

Run Analytics Seamlessly Across Multi-Cloud Environments with DataOps

Run Analytics Seamlessly Across Multi-Cloud Environments with DataOps

Data analytics is performed using a seemingly infinite array of tools. In larger enterprises, different groups can choose different cloud platforms. Multi-cloud or multi-data-center integration can be one of the greatest challenges to an analytics organization....

Environments Power DataOps Innovation

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,...

Gartner: DataOps Enables Remote Work

Gartner: DataOps Enables Remote Work

Although work restrictions are being lifted around the country, the office work environment will probably never be the same.  Many companies are allowing employees to work remotely through the end of the year, until they are comfortable returning, or even forever...

A Tool-Agnostic Approach to DataOps Using the DataKitchen Platform

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...

Predicting the Failure of Quantum Computing

Predicting the Failure of Quantum Computing

Quantum computing will fail before it succeeds. That’s not a criticism of quantum computing. It’s more a commentary on the difficulty of deploying solutions based on cutting-edge innovation. In 2020, the human species has extensive experience with new technologies. I...

For Data Team Success, What You Do is Less Important Than How You Do It

For Data Team Success, What You Do is Less Important Than How You Do It

In today’s on-demand economy, the ability to derive business value from data is the secret sauce that will separate the winners from the losers.  Data-driven decision making is now more critical than ever.  Analytics could mean the difference between finding the right...

4 Easy Ways to Start DataOps Today

4 Easy Ways to Start DataOps Today

The primary source of information about DataOps is from vendors (like DataKitchen) who sell enterprise software into the fast-growing DataOps market. There are over 70 vendors that would be happy to assist in your DataOps initiative. Here’s something you likely won’t...

Why Are There So Many *Ops Terms?

Why Are There So Many *Ops Terms?

A Guide to Ops Terms and Whether We Need Them It is challenging to coordinate a group of people working toward a shared goal. Work involving large teams and complex processes is even more complicated. Technology-driven companies face these challenges with the added...

Add DataOps Tests to Deploy with Confidence

Add DataOps Tests to Deploy with Confidence

DataOps is the art and science of automating the end-to-end life cycle of data-analytics to improve agility, productivity and reduce errors to virtually zero. The foundation of DataOps is orchestrating three pipelines: data operations, analytics development/deployment...

Writing DataOps Tests with the DataKitchen Platform

Writing DataOps Tests with the DataKitchen Platform

Tests identify data and code errors in the analytics pipelines. Automated orchestration of tests is especially important in heterogeneous technical environments with streaming data. The DataKitchen Platform makes it easy to write tests that check and filter data...

Open Source Data Observability Software

DataOps Observability: Monitor every Data Journey in an enterprise, from source to customer value, and find errors fast! [Open Source, Enterprise]

DataOps Data Quality TestGen: Simple, Fast Data Quality Test Generation and Execution. Trust, but verify your data! [Open Source, Enterprise]

DataOps Software

DataOps Automation: Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change. [Enterprise]

recipes for dataops success

DataKitchen Consulting Services


Assessments

Identify obstacles to remove and opportunities to grow

DataOps Consulting, Coaching, and Transformation

Deliver faster and eliminate errors

DataOps Training

Educate, align, and mobilize

Commercial Data & Analytics Platform for Pharma

Get trusted data and fast changes to create a single source of truth

 

dataops-cookbook-download

DataOps Learning and Background Resources


DataOps Journey FAQ
DataOps Observability basics
Data Journey Manifesto
Why it matters!
DataOps FAQ
All the basics of DataOps
DataOps 101 Training
Get certified in DataOps
Maturity Model Assessment
Assess your DataOps Readiness
DataOps Manifesto
Thirty thousand signatures can't be wrong!

 

DataKitchen Basics


About DataKitchen

All the basics on DataKitchen

DataKitchen Team

Who we are; Why we are the DataOps experts

Careers

Come join us!

Contact

How to connect with DataKitchen

 

DataKitchen News


Newsroom

Hear the latest from DataKitchen

Events

See DataKitchen live!

Partners

See how partners are using our Products

 

Monitor every Data Journey in an enterprise, from source to customer value, in development and production.

Simple, Fast Data Quality Test Generation and Execution. Your Data Journey starts with verifying that you can trust your data.

Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change.