The Corona COVID-19 virus has completely changed the landscape for business in 2020. Strategic plans that were approved a few short months ago are being scrapped. With a recession at hand, it’s time to hit the reset button on your plans. Business thought leaders were...
DataOps places great emphasis on productivity. Team velocity can improve significantly when the data organization uses tools and methods that promote component reuse. Architecting analytics as microservices is one way to stimulate code reuse. The challenge is that the...
For more information on DataOps, checkout: The DataOps Manifesto DataOps Cookbook DataOps Videos DataOps News DataOps Blog DataOps SlideShare
DataOps is a hot topic these days. It's not surprising given that DataOps holds true potential for enabling enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to slash cycle times...
We often hear people say that DataOps is just automating the data pipeline — using orchestration to execute directed acyclic graphs (DAGs). Enterprises may already use orchestration tools (Airflow, Control-M, etc.) and mistakenly conclude that they have DataOps...
Organizational complexity creates significant problems, but executives in a McKinsey Survey showed little understanding of the types of complexity that create or destroy shareholder value. In their research, McKinsey identified two types of complexity: Institutional...
Have you ever failed at work? Most people have done something cringeworthy at some point. I have plenty of funny stories to tell. There’s the time I set off the fire alarm on my first day of a new management job. Perhaps even more notable are the epic fails. I once...
Breaking Through the Noise A Guide to Understanding DataOps Solutions DataOps is the hot topic on every data professional’s lips these days, and we expect to hear much more about DataOps in 2020. This is not surprising given that DataOps holds true potential for...
Leading software companies perform millions of code releases per year. Typical data-analytics organizations perform less than 10. This gap explains why most data-analytics projects fail to deliver. Without the capability to move at lightning speed, data analytics...
As recently as eighteen months ago, we would mention “DataOps” and get blank stares. As recently as eighteen months ago, we would mention “DataOps” and get blank stares. Today, analyst firms Gartner, Eckerson, 451, and Forrester publish extensively on DataOps and...
Announcing Open Source DataOps Data Quality TestGen 3.0
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.