How are organizations building modern data platforms that balance scalability?
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How are organizations building modern data platforms that balance scalability?
Q: How are organizations building modern data platforms that balance scalability, governance, real-time analytics, and AI readiness without adding too much complexity?
Weāre exploring how to design a modern data platform solution that integrates well with Dynamics 365 and other Microsoft technologies while still staying scalable and manageable long term.
With data coming from multiple sources like cloud apps, on-prem systems, and IoT devices, companies need platforms that support ingestion, storage, transformation, and analytics in a unified way. At the same time, they must handle data governance, security, quality, and compliance while still enabling self-service access for business users.
Iām curious how teams are making key architecture decisions ā such as lake vs. warehouse vs. lakehouse ā and how they avoid tool sprawl and rising cloud costs. How are you preparing your platform for AI and real-time use cases, and what challenges or lessons have stood out during implementation?
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