First, give conclusions that can be used for decision-making
If the client has multiple names in CRM, ERP and financial systems, first and foremost the main data problem; if the income and order indicators of the various departments differ in calibre, the indicator and data governance; if the quality of the task is reduced after RAG refers to the expired system, Agent over-authorization of documents or model updates, then it is within the scope of AI data governance. A production AI application often relies on three tiers of capability at the same time, and therefore should not create a separate “AI data” that is completely isolated from the original data system. The correct approach is to identify the primary data and object identifiers, to re-use the existing integration, cataloguing, quality and access capabilities, and to add to document processing, knowledge indexing, task evaluation and model application logs.
What conditions need to be identified before judgement is made?
The same question may have different answers under different business, data and project phases. It is suggested that the following conditions be checked and that the common findings on the web be incorporated into their own projects.
Suggested order of advance
First, we'll be clear about the target and the border.
Take stock of existing MDM, silos, data platforms and document systems.
Validation Key Dependence
Reusable and missing governance capacity by AI assignment.
Development of assessable outcomes
Priority is given to the completion of privileges, versions, knowledge and assessment of closed rings.
Make sure you decide the next step with the real results.
Harmonize responsibility and operational indicators to avoid creating new data islands.
How do you understand it in the actual business?
The enterprise has a data warehouse and BI, but the client RG still answers the old product policy. The reason is not lack of a data platform, but the validity of the document, the release of knowledge, and the return of the RG are not included in governance.
The easiest pit to step on.
Rebuild AI data governance as stand-alone platform
MDM code only, no business position ongoing
Only the database is governed, and no files and sample assessments are managed
How should we end up receiving and confirming?
The governance blueprint should identify whether each capacity is reused or newly built from existing platforms and who maintains the target, indicators, knowledge, competencies and assessments, respectively, avoiding multiple sets of calibres and overlapping responsibilities.
When preparing to communicate with suppliers or internal teams, it is recommended that current processes, representative samples, existing systems, planning time and budget levels be brought. First, the unknown items are clearly marked, and then the decision is made to use diagnostics, PoC, fixed-range projects or ongoing research and development, which is usually more reliable than a direct demand for a price and duration without borders.