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Cloud Architecture proposition is based on business needs, current organizational context and legal requirement.
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Contextualization
- Scanning the files based on legal criteria.
- After scanning, cleaning the files based on legal criteria : what we have to keep and what we can delete.
- Organizing the files in forlders (classification, structuration, etc.) and in parallel, finalize the segmentation (access to the files by department).
- Once it’s done, storing the active files and archiving the inactive files which have to be kept (legal criteria).
Implementation steps
- Milestone 1 : the process of scanning files in a physical location.
- Milestone 2 : the process of storing and archiving.
- Milestone 3 : the process of searching data & information (no-manual, fast and accurate).
Case scenarios (according Microsoft)
Microsoft proposes a list of case scenarios regarding the use of AI technologies : GitHub - Azure/ai-solution-accelerators-list: This is a list of the Azure AI Solution Accelerators available to demonstrate and simply deployment of Azure AI
- Operationalization and management of predictive models (Machine Learning scenario).
- Regular detection of rapid data change (Machine Learning scenario).
- Accurate and intensive data research (Cognitive Search, Speech, etc…).
- Automated business process requiring data transformation steps (Coginitive Services, Speech, etc…).
- Collection of external and internal data to support decision-making (Text Analytics, Translator, etc…).
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This is a case of accurate and intensive data search or data mining.
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Organizational directives and guidelines
No information could be mentionned because it’s belonging to the company (directives regarding internal compliance, directives regarding personal data protection).