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
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.
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.
The Race For Data Quality in a Medallion Architecture
DataOps Observability: Monitor every Data Journey in an enterprise, from source to customer value, and find errors fast! [Open Source, Enterprise]
DataOps Data Quality TestGen: Simple, Fast Data Quality Test Generation and Execution. Trust, but verify your data! [Open Source, Enterprise]
DataOps Automation: Orchestrate and automate your data toolchain to deliver insight with few errors and a high rate of change. [Enterprise]
DataOps Consulting, Coaching, and Transformation
Commercial Pharma Agile Data Warehouse
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.