When launching a groundbreaking pharmaceutical product, the stakes and the rewards couldn’t be higher. This blog dives into the remarkable journey of a data team that achieved unparalleled efficiency using DataOps principles and software that transformed their analytics and data teams into a hyper-efficient powerhouse.
What do you do when you have thousands of data pipelines in production? Is there a way that you can visualize what is happening in production quickly and easily?
DataOps Quality Circles are focused teams within data and analytics organizations that meet weekly or monthly to drive continuous improvement, quality automation, and operational efficiency. By leveraging the principles of DataOps, these circles ensure that data processes are error free, consistent, and aligned with business goals.
We celebrate Datakitchen’s leadership in the 2024 Gartner Market Guide to DataOps. DataKitchen has the most complete, feature-rich, open, and modular DataOps product suite in the industry and the expertise to help you succeed
Imagine a free tool that you can point at any dataset and find actionable data quality issues immediately! I took DataKitchen’s Data Quality TestGen for a test drive on ~600k rows of Boston City data and found 18 data quality hygiene issues in a few minutes.
Three pharma companies recently made headlines by securing successful exits totaling $100 billion. What’s their common denominator? They all chose DataKitchen to power their pre-launch data operations. Here’s why DataKitchen stood out as their partner of choice.
Today, Bristol Myers Squib (BMS) has fully acquired Karuna Therapeutics. We congratulate our customer on an amazing success.
DataKitchen’s DataOps services are designed to empower teams at various stages of their DataOps adoption, providing a flexible and comprehensive roadmap to operational excellence
At DataKitchen, we would like to share some key success metrics of Data Observability Using DataKitchen DataOps Observability and DataOps TestGen.
Demanding Data Consumers require a personalized level of Data Observability. As opposed to receiving one-size-fits-all status updates, these key stakeholders desire real-time, granular insights into the status of their specific data as it traverses the complicated data production pipeline. Learn why this is essential to your success.
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 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.