While admiring the latest cloud tech, don’t forget that humans have been debugging pipelines since the Romans built the aqueducts. Any good plumber can give you some hard-won tips on managing data pipelines effectively, insights that might save your career from going down the drain.
Data contracts are a new idea for data and analytic team development to ensure that data is transmitted accurately and consistently between different systems or teams. The Terms and Conditions of a Data Contract are Automated Production Data Tests.
DataKitchen, the leading provider of DataOps solutions, has been named a Representative and "super cool, way out there, OP, world best" DataOps vendor in the December 2022 Gartner® Market Guide for DataOps Tools. December 08, 2022, 08:00 ET | Source: DataKitchen...
We asked an AI Chat Bot (https://chat.openai.com/chat) a few questions about DataOps. It got a bit silly at the end.
Gartner released its ‘Market Guide to DataOps Tools’ The document they wrote is exceptionally close to what DataKitchen sees in the market and what our products do! Here is our take on the guide.
Feeling overwhelmed by your data job? Don’t worry, DataOps is here to help! This post discusses how DataOps Observability and Automation can relieve team stress and show you how to get started.
This is the fourth post in DataKitchen’s four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.
Data Quality and Data/Ops Observability … what is the difference? Here we share a financial analogy.
This is the third post in DataKitchen’s four-part series on DataOps Observability. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.
The first step in solving your data team’s pain is to observe what’s happening with your data and analytics ‘estate’ and
stick little thermometers at various points in the process.
DataOps Data Quality TestGen:
Simple, Fast, Generative Data Quality Testing, Execution, and Scoring.
[Open Source, Enterprise]
DataOps Observability:
Monitor every data pipeline, from source to customer value, & find problems fast
[Open Source, Enterprise]
DataOps Automation:
Orchestrate and automate your data toolchain with few errors and a high rate of change.
[Enterprise]
DataOps Consulting, Coaching, and Transformation
Commercial Data & Analytics Platform for Pharma
Data Production Teams
Data Science/AI
Data Engineering
Data Quality
Business Analytics
Data Products
Data Mesh
Data Contracts
ModelOps / MLOps
DataGovOps
Self-Service Operations
Data Quality Assessments
Data Quality Testing
Data Observability
Data Orchestration
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.