Data Strategy

Almost every AI project reaches a point where the pilot works and the demo is convincing. The agent does what you hoped it would. Yet the transition to ...

At agricultural wholesaler Kramp, analytics engineers shifted from a human-first to an AI-first strategy in just nine months. A task that previously took three ...

1,000 invalid records may matter less than one criticalerror

Why metadata and data definitions are the silent dealbreakers of data-driven working. Data-driven working often gets bogged down by culture, ownership, and ...

Important decisions about your data pipeline that separate an AI pilot from a system in production. Every AI project arrives, sooner or later, at the same ...

Why reliable data starts with shared understanding, ownership, and repeatability Many organizations now have a data platform in place. Data is extracted from ...

Organizations are investing heavily in data, analytics, and AI. However, turning these ambitions into tangible results remains a challenge. Choosing a ...

Why fragmentation keeps data‑driven working stubbornly stuck Data‑driven working often gets blocked by culture and ownership. Data is quickly seen as an IT ...

The opportunities AI brings are massive, bigger than most professional services organizations even realize at this point. But it also brings hard challenges. ...

Based on our hands-on experience at BearingPoint, this article shares what it actually takes to make AI work in large, complex organizations. Find us at Data ...