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Data & AI
Data platforms, governance and practical enterprise AI adoption.
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Data & AI · Decision guide
Integration platform or custom code? Compare the work after the first failure
Compare iPaaS and custom integration through retries, schema changes and recovery. Connector availability is only the beginning of the operating-cost decision.
Data & AI · Decision guide
Build, buy or extend AI: choose the work your team should own
Compare building, buying and extending AI against the same business task. Expose the integration, evaluation and support work each option leaves with your team.
Data & AI · Practical guide
An API inventory should tell you whether the old version can be retired
Build an API inventory from deployment, gateway and traffic evidence. Confirm owners and consumers so an obsolete version can be retired without breaking service.
Data & AI · Explainer
Enterprise AI governance should follow the authority a system is given
Build AI governance around the workflow, data, decision authority and evidence needed for deployment, then review changes that alter those boundaries.
Data & AI · Explainer
Data governance gives business meaning an accountable owner
Build data governance around definitions, decision authority and fitness for use, then choose tools that support those responsibilities.
Data & AI · Practical guide
Shadow AI: solve the work problem behind the unapproved tool
Review shadow AI by establishing the task, the data and the limits of the discovery evidence. Close the case with an alternative people can actually use.
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