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CommunityData engineering & the warehouse/lakehouseAzure Data FactoryDatabricks
r/dataengineering · Read source ↗

A consulting company is working with a client to modernize their data environment. The client currently extracts data from on-premises databases like Oracle, SQL Server, and Postgres using Azure Data Factory (ADF) to transfer it into Azure Data Lake Storage (ADLS), followed by processing with Databricks.

MyDataWork POV — The notion of 'modernizing' by simply moving from on-prem to cloud raises more questions than it answers. What's missing is clarity on how this transition tackles data governance, latency, or even cost-effectiveness. Azure Data Factory and Databricks are potent tools, but are they the right fit for every legacy system being uprooted? Without dissecting the specific constraints and ambitions of the current workflow, this 'cloud-first' mantra feels like a glossy overcoat on a yet-to-be-proven structure.
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