Data analytic team war rooms, often convened for emergency problem-solving, epitomize inefficiency and detract from proactive, value-driven tasks. By leveraging data observability and rigorous testing, issues can be detected and resolved early, negating the need for such reactive measures in the modern era of DataOps.
How DataOps is Transforming Commercial Pharma Analytics
DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from...
Data Journey First DataOps
‘Data Journey First DataOps’: it’s a revolution in which every data, tool, server, and step becomes part of a meaningful story, enhancing our data initiatives’ overall value, impact, and trust.
UPCOMING WEBINAR: Automated Test Generation – Why Data Teams Need It
This webinar discusses how to make embarrassing data errors a thing of the past.
We will start with how data engineers do not understand their data and have difficulty identifying problematic data records. We will also discuss how the vast majority of data engineers are so busy that they don’t know, or have time to write, tests to write to find data errors. We will finish with a demonstration of DataKitchen’s New DataOps Testgen Product.
That missing piece that connects data system expectations and reality is a ‘Data Journey.’ It is the missing piece of our data systems.
ON-DEMAND WEBINAR: Data Journey – The Missing Piece
Something is missing from our data systems. We cannot judge the expectations vs. reality in our production data systems. What is the variance between what is happening now and what should be happening? Is it on time? Late? Is it trustworthy? What is happening now? Will my customers find a problem?
That missing piece that connects data system expectations and reality is a ‘Data Journey.’ It is the missing piece of our data systems.
Why I Chose DataKitchen for DataOps
Why choose DataKitchen? During my nearly seven-year tenure leading an analytics function at Celgene, our partnership with DataKitchen was a critical component of my team’s data and analytics strategy. DataKitchen preaches the message of DataOps, a philosophy they...
ON-DEMAND WEBINAR: Managing Stress in Data Engineering: Data Quality and Testing Techniques for Data Observability
Why do 78% of data engineers wish their job came with a therapist to help manage work-related stress? THEY DO NOT TEST.
DataKitchen named: “super cool, way out there, OP, world best” DataOps vendor
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...
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.