It’s never good when your boss calls at 5 pm on a Friday. “The weekly analytics didn’t build correctly. What happened? Call me every hour with updates until you figure it out!” For many data professionals, this situation is all too familiar. Analytics, in the modern...
Curious about what DataOps capabilities your organization already has or how you stack up? DataKitchen published a white paper Launch Your DataOps Journey with the DataOps Maturity Model (which you can download here) to guide you on benchmarking your org's DataOps...
So you've learned about DataOps and want to get begin implementing it? Look no further than DataKitchen's white paper The Seven Steps to Implement DataOps (which you can download here)! We've taken the seven steps to implement DataOps and included them in the...
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,...
We’ll show why and how to orchestrate your multi-environment and multi-tool Production (aka ‘Value’) pipelines along the entire journey – from data access to value delivery.
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...
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...
How much of your time do you spend writing tests? In a DataOps enterprise, data professionals spend 20% of their time writing tests. This may seem like a lot, but if an organization is wasting time due to errors, every hour spent on tests saves many hours in lost...
The Race For Data Quality in a Medallion Architecture
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 Automation: Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change. [Enterprise]
DataOps Consulting, Coaching, and Transformation
Commercial Pharma Agile Data Warehouse
Data Production Teams
Data Science/AI
Data Engineering
Data Quality
Business Analytics
Data Products
Data Mesh
Data Contracts
ModelOps / MLOps
Data Observability
DataGovOps
Self-Service Operations
Hybrid Cloud Architectures
Cloud Architectures
Kubernetes Architectures
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.