A Conceptual Model for ETL Design and Data Integration in Salesforce-Centric Enterprise Architectures

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@article{1717560,
      author = {Olaniyi Badmus, Adetomiwa A. Dosunmu, David Excel Ozowara},
      title = {A Conceptual Model for ETL Design and Data Integration in Salesforce-Centric Enterprise Architectures},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {3},
      number = {5},
      pages = {565-579},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1717560.pdf},
      abstract = {Enterprise organizations increasingly position Salesforce as a central engagement and data management hub in complex multi-system architectures, creating a need for rigorous approaches to extract, transform, and load (ETL) design that account for the distinctive structural properties of the Salesforce data model. Traditional ETL frameworks were designed for relational data warehouse environments and do not directly address the object-relationship model, governor limits, bulk API constraints, and metadata-driven customization capabilities that characterize Salesforce as a data integration target. This paper proposes a conceptual model for ETL design and data integration in Salesforce-centric enterprise architectures. The model establishes five conceptual dimensions: source data profiling and quality assessment, transformation logic design for Salesforce object alignment, bulk API utilization strategy, data lineage and audit trail maintenance, and ongoing data quality governance. Each dimension is articulated through design principles, decision criteria, and illustrative patterns drawn from enterprise data integration practice. The model addresses both inbound data flows, in which external source data is loaded into Salesforce, and bidirectional synchronization scenarios, in which Salesforce data participates in enterprise-wide data exchange with downstream analytical, operational, and clinical systems. The conceptual model is positioned as a bridge between established data warehousing and ETL literature and the Salesforce-specific implementation guidance that currently dominates practitioner discourse.},
      keywords = {ETL Design, Salesforce Data Integration, Bulk API, Data Quality Governance, Enterprise Data Architecture, Data Lineage, CRM Data Management},
      month = {November},
  }