Lineage: Break Into Data Governance — Making Company Fit for AI, and the Career Behind Every Failed AI Project (A Field Guide)

Every company wants to point AI at its own data. Then they find out what is in it.Nobody can say where a number came from, which copy is authoritative, or whether the model is even allowed to read it. Gartner predicts organisations will abandon 60% of AI projects that are not supported by AI-ready data through 2026, and found 63% either do not have - or do not know whether they have - the data management practices AI needs (Gartner, February 2025). The people who fix that are data governance professionals.This book is written first for people at the start - graduates and early-career workers watching entry-level ads demand experience nobody will give them. Data governance is one of the few professional doors where a deliberate beginner can arrive credible, because the qualifying knowledge is published and the work products can be practised before anyone employs you. Career changers from analyst, BA, DBA, records and compliance backgrounds are mapped too, but the on-ramp is built for someone starting out.You will produce real artefacts from public data in the first chapter: a data dictionary and a quality assessment, done with a spreadsheet, no budget and no permission. That is the honest answer to the experience trap - not encouragement, but evidence you can show.There is a genuine credential too: DAMA International's CDMP, built on the DMBOK - a professional qualification rather than a vendor badge, and one you can begin without an employer's blessing.It is equally about how data functions are changing: from a committee that says no, to the team that makes data usable on purpose - definitions, catalogues and lineage a model can be trusted against. Pay is handled honestly: no government wage series isolates this role, so figures are named for what they are, with the warning that a first role pays well below them. An Australian appendix covers the local regime separately.The model gets the credit. The data decides the outcome.