Over time, organizations that adopt multiple integration technologies (e.g., different ETL tools, APIs, middleware, data buses, etc.) often end up with a highly complex and fragmented integration landscape. Each technology may have its own protocols, standards, monitoring tools, and maintenance requirements. This leads to:
Increased technical debt
Redundancy in integration logic
Higher costs for maintenance and support
Difficulty in scaling or adapting new systems
Lack of consistency in data flow and transformation
This complexity is a common symptom of uncoordinated integration efforts over time, often arising in the absence of centralized data architecture or integration governance.
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