7 questions every CTO, CDO, and VP of Engineering should answer before their next data infrastructure investment — and what the answers reveal about your readiness for AI.
100% free · Written by practitioners with 134+ years of combined experienceMost organizations spend millions on data infrastructure and still can't answer basic business questions in real time. This guide cuts through the noise with the diagnostic questions we use with Fortune 500 clients before any engagement — so you can assess your own readiness honestly.
Can your entire organization agree on one number for any key metric? If not, why — and what does it cost?
Is your data clean, labeled, and governed well enough to train a model on it today? Most aren't — find out where you stand.
Can you identify, in under 5 minutes, which workload caused last month's cloud bill to spike?
When a pipeline breaks at 2 AM, how long until a human knows? What's the business cost of that delay?
If a regulator asked you today who has access to what data and why — could you answer in 24 hours?
Is your data team firefighting or building? What % of sprint capacity goes to maintenance vs. innovation?
What decisions made 3 years ago are slowing you down today — and what will they cost to address in 2 more years?
The 7-question framework above is just the start. The full playbook includes scoring rubrics, recommended technology patterns for each scenario, and a self-assessment you can share with your team. Optional — we'll also send you practical data architecture insights twice a month.
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