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Resources

Reading, listening, and watching from the pharma practice.

Real launches, real platforms, real numbers. Case studies, white papers, webinars, and writing — most pull from the main DataKitchen site so they stay co-located with the broader product and methodology content.

blogs

Blogs

The $100 Billion Secret

Blog

Why leading pharma companies outsource their commercial data teams: specialized focus, speed, simplicity, and transparency over generalist IT.

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How DataOps is Transforming Commercial Pharma Analytics

Blog

The first 6–12 months of a launch determine its lifetime revenue. The Otezla story: 7 engineers, 10–12 analysts, hundreds of datasets, tens of thousands of tests.

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Implementing a Pharma Data Mesh using DataOps

Blog

How DataOps automation makes data-mesh architectures viable in commercial pharma — not as a slogan, but as something engineering teams can actually ship and operate.

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The Equation for AI Success: DT + Dx + Ctx = 10×

Blog

Where AI lands in commercial pharma analytics. Data transformation, data exposure, and context: the three terms that turn an AI investment into measurable team productivity.

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DataOps FITT: Data Testing for 10× Data Engineering Productivity with AI

Blog

A practical look at how AI-assisted test generation reshapes commercial pharma data engineering — with a pharma example walked end-to-end.

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Reinvent Marketing Automation with the DataKitchen DataOps Platform

Blog

A non-personal-promotion story. How an integrated commercial data platform reset the team's relationship with marketing campaign data, channel ROI, and budget decisions.

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Why I Chose DataKitchen

Blog

A practitioner's view from inside a commercial pharma analytics team. What "transparent, transferable, specialized" actually feels like day-to-day.

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Congratulations to the Karuna Team on Their Acquisition

Blog

A note marking the Karuna → BMS acquisition, with reflection on what made the underlying commercial data work so durable through the transition.

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Want a deeper conversation?

The writing only tells part of the story. Half an hour with our team will get you specifics on your stack, your launch window, and what the first sprint would look like.