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.
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...
Announcing the DataOps Cookbook, Third Edition
The new idea showcased in the third edition of the DataOps Cookbook is to focus first on understanding and observing the journey that data takes through your production environment – from ingestion to processing to delivering actionable insights. The DataOps Cookbook-‘Data Journey First DataOps’ Third Edition
A Summary Of Gartner’s Recent Innovation Insight Into Data Observability
On 20 July 2023, Gartner released the article “Innovation Insight: Data Observability Enables Proactive Data Quality” by Melody Chien.
DataKitchen Summarizes and comments
The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure
The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. Is it overkill? Paradox of choice? Or the right tool for the right job? We discuss.
The Syntax, Semantics, and Pragmatics Gap in Data Quality Validation Testing
What is the full range of data quality validation tests for data at rest and data in use? Linguistics provides an organizing principle: syntax, semantics, and pragmatics
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.
Introducing The Five Pillars Of Data Journeys
The “Five Pillars of Data Journeys” outline a comprehensive approach to tracking and monitoring data across its lifecycle.
Why the Data Journey Manifesto?
Why the Data Journey Manifesto?
So why another manifesto in the world? Really? Why should I care?
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.