Data from various sources (databases, APIs, files, connected objects, etc.) is collected and transformed by automating its ingestion, cleaning, structuring, and enrichment to make it reliable, consistent, and directly usable.
• Automated and robust data pipelines are developed and maintained to ensure smooth, secure, and efficient access to data.
• Data flow quality and security controls are implemented, integrating validation, monitoring, and traceability mechanisms.
• Data flows are modeled and structured in accordance with architectural standards, security and confidentiality rules (e.g., GDPR, internal policies) and are documented to ensure the maintainability of solutions.
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