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Abstract
In the age of data-driven decision-making, Salesforce dashboards have emerged as a cornerstone for real-time analytics in enterprise environments. However, integrating heterogeneous data sources into a unified and scalable dashboard framework remains a critical challenge. This paper proposes a modular, cloud-compatible data integration framework tailored for Salesforce environments that supports high-volume, multi-source data ingestion while preserving data fidelity and system performance. Through a synthesis of current research and architectural models, this paper addresses scalability bottlenecks and outlines best practices in real-time data transformation and visual rendering within Salesforce. Emphasis is placed on ETL pipelines, API-based connectivity, and schema-flexible data lakes to support elasticity and performance.
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