Why the Data Journey Manifesto?
So why another manifesto in the world? Really? Why should I care?
Why the Data Journey Manifesto?
So why another manifesto in the world? Really? Why should I care?
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.
Chris Bergh, CEO of DataKitchen, delivered a webinar on two themes – Data Products and Data Mesh. Bergh started by discussing the complexity within data and analytics teams, stating that complexity makes everything more complicated and, in the long run, it kills productivity.
In the webinar “Driving Data Analytic Team Excellence Through Agility, Efficiency, and Aphorisms,” James Royster, Vice President of Commercial Operations, Insights, and Analytics at Karuna Therapeutics, shared his insights on leading efficient and effective data analytics teams.
You spend all day helping your customers leverage analytics for improved business performance, so why are you so un-analytic about how you run your data analytics teams? Where is your data and analytic team metrics report?
The real problem in data analytics is that teams need to
deliver insight to their customers without error
put new ideas into production rapidly
minimize their ‘insight manufacturing’ expenses
… all at the same time
Gartner released the article “5 Ways to Enhance Your Data Engineering Practices.” By Robert Thanaraj, Ehtisham Zaidi, and 2 more. DataKitchen gives its perspective.
Data Quality and Data/Ops Observability … what is the difference? Here we share a financial analogy.
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...
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.
DataOps Data Quality TestGen:
Simple, Fast, Generative Data Quality Testing, Execution, and Scoring.
[Open Source, Enterprise]
DataOps Observability:
Monitor every date 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
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.