Data Quality and Data/Ops Observability … what is the difference? Here we share a financial analogy.
A Data Prediction for 2025
What will the world of data tools be like at the end of 2025? The crazy idea is that data teams are beyond the boom decade of “spending extravagance” and need to focus on doing more with less.
“You Complete Me,” said Data Lineage to Data Journeys.
The benefits of a long-lasting relationship between Data Journeys and data lineage can help give a complete view of your data operations. Both tools help deliver more trusted insight to your customer.
Plumbing Wisdom for Data Pipelines
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.
The Terms and Conditions of a Data Contract are Data Tests
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.
An AI Chat Bot Wrote This Blog Post …
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 Market Guide to DataOps Software
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.
DataOps Observability and Automation to the Rescue!
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.
DataOps Observability: Taming the Chaos (Part 4)
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.
Question: What is the difference between Data Quality and DataOps Observability?
Data Quality and Data/Ops Observability … what is the difference? Here we share a financial analogy.
