Data Integration Patterns for Data Warehouse Automation

  • Kalle Tomingas
  • Margus Kliimask
  • Tanel Tammet
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 312)


The paper presents a mapping-based and metadata-driven modular data transformation framework designed to solve extract-transform-load (ETL) automation, impact analysis, data quality and integration problems in data warehouse environments. We introduce a declarative mapping formalization technique, an abstract expression pattern concept and a related template engine technology for flexible ETL code generation and execution. The feasibility and efficiency of the approach is demonstrated on the pattern detection and data lineage analysis case studies using large real life SQL corpuses.


data warehouse etl data mappings template based sql generation abstract syntax patterns metadata management 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Kalle Tomingas
    • 1
  • Margus Kliimask
    • 2
  • Tanel Tammet
    • 1
  1. 1.Tallinn University of TechnologyTallinnEstonia
  2. 2.Eliko Competence CenterTallinnEstonia

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