First, give conclusions that can be used for decision-making
The data need to be structured in terms of object identification, field calibre, time and primary responsibility; documents need source, version, validity, scope of application and permission; photographic voice needs to be collected under conditions, categories and authorizations; assessment samples also need to cover normal, abnormal, unquestioned, ultra vires and high-risk situations. Data quality cannot be detached from the average calculation of operational risk, such as a small number of critical price errors that may be more severe than the absence of a large number of common fields. Once governance is complete, an independent task set should be frozen, comparing AI with changes in references, answers, tools and operational results.
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.
Define target tasks and serious errors.
Validation Key Dependence
Creates a data document quality and permission check sheet.
Development of assessable outcomes
Quality and ultra vires testing is done using a stand-alone task set.
Make sure you decide the next step with the real results.
A data update, retreat and re-evaluation exercise.
How do you understand it in the actual business?
The list of documents is very large, but not suitable for question and answer. The enterprise’s supplementary version is considered to be the first AI-ready knowledge after application, downline content, and an answerless test is established. The examples do not represent the performance of a particular client, and the actual conclusions need to be verified in conjunction with the enterprise’s own business volume, sample, system and liability boundaries.
The easiest pit to step on.
The bigger the data, the better it is for AI.
We'll have to use a training sample to complete the inspection and inspection.
Update failed without warning, index long-term in old version
How should we end up receiving and confirming?
The receipt and inspection material should include the calibre of the object, source version, permission, quality rules, record of failure, independent task set and item-by-case results, and demonstrate that the enterprise personnel can update, retreat and re-run the evaluation.
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.