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.
All the cool kids are talking about Data Products and Data Mesh. The data companies have gotten ahold of terms and started to say their twenty-year-old ETL tools are the perfect tools to do that fashionable product-meshy stuff. What is going on?
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.
James guides us through years of experience working in data, giving insight to many customers and leading highly efficient and effective teams. Driving Data Analytic Team Excellence Through Agility, Efficiency, and Aphorisms
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.
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 can’t talk to your stakeholders if your pipelines are down. You can’t get good quality sleep if your data products brake in the middle of the night. You can’t earn the trust of your stakeholders if it takes you weeks to make even the smallest change without braking things
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
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.
