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...
Data organizations don’t always have the budget or schedule required for DataOps when conceived as a top-to-bottom, enterprise-wide transformational change. An essential part of the DataOps methodology is Agile Development, which breaks development into incremental...
Adopting DataOps can be easy; by following DataKitchen’s ‘Lean DataOps’ four-phase program, you can roll out DataOps in smaller, easy-to-manage increments.
“How do you make it so that your data and analytics team can get the ideas from their heads into production quicker? How do you create a process like a factory that produces Toyotas and not AMC Pacers? How can you get these teams who work all over the company to collaborate better? Those are the problems that DataOps solves.”
Learn about DataOps from data leaders Jim Tyo, Invesco CDO; Kurt Zimmer, AstraZeneca Head of Engineering for Data Enablement & Ryan Chapin, former GE exec.
In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK); and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise...
Jonathan Hodges of Workiva and Chuck Smith of GlaxoSmithKline join DataKitchen’s Chris Bergh to discuss their DataOps journey and key lessons learned along the way.
Every DataOps initiative starts with a pilot project. How do you choose a project that matters to people? DataOps addresses a broad set of use cases because it applies workflow process automation to the end-to-end data-analytics lifecycle. DataOps reduces errors,...
As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. Centralizing analytics brings it under control but granting analysts free reign is necessary to foster innovation and...
Savvy executives maximize the value of every budgeted dollar. Decisions to invest in new tools and methods must be backed up with a strong business case. As data professionals, we know the value and impact of DataOps: streamlining analytics workflows, reducing errors,...
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.