The New DNA of the Data + AI Team
By Shane Murray
A new kind of data + AI team is emerging—one that’s deeply aware that today’s AI applications demand not just intelligence, but trust.
What is AI-Ready Data? Redefining AI-Ready for Production.
By Shane Murray
Building Reliable Foundations for Data + AI Systems It’s no big revelation that data teams are being challenged to do more with AI. But while deploying an AI prototype has never been easier, operating those applications safely in production is harder than ever. Achieving high-quality data remains one of the most critical components for trustworthy … Continued
The Top 5 AI Reliability Pitfalls
By Shane Murray
Hallucination—when an AI confidently generates false or nonsensical outputs—is the most notorious failure mode for AI applications. But is it really the one you need to worry about? A lot of noise has been made about hallucinations in recent months. As more companies introduce AI into production, the issue of hallucinations is perennially in the … Continued
How To Implement Data Mesh: Top Tips From 4 Data Leaders
By Shane Murray
Four data leaders from leading organizations give their practical advice on how to implement data mesh.
Organizing Generative AI Teams: 5 Lessons Learned From Data Science
By Shane Murray
LLMs hold tremendous promise, but generating sustainable value will require some thought as to how you organize generative AI teams.
Conscious Decoupling: How Far Is Too Far For Storage, Compute, And The Modern Data Stack?
By Shane Murray
While there is no right answer, there is likely a sweet spot for most organizations’ data platforms. Read on to see where that might be.
Who Is Responsible For Data Quality? 5 Different Answers From Real Data Teams
By Shane Murray
Specialists or generalists? Engineer or analyst? We examine who is responsible for data quality and different team structures used by real data teams.
Experimentation: How Data Leaders Can Generate Crystal Clear ROIÂ
By Shane Murray
Data teams can drive quantifiable ROI by establishing a strong experimentation program. Here are the lessons we’ve learned at Airbnb, the New York Times, and other stops along the way.
The Chaos Data Engineering Manifesto: Spare The Rod, Spoil Prod
By Shane Murray
Chaos data engineering is another lesson we can learn from software engineers: break stuff to make it more reliable.
Meaningful Product Experimentation: 5 Impactful Data Projects for Building Better Products
By Shane Murray
How data teams and product leaders can do product experimentation right and other impactful data projects for building better products.