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DECIDE: An Agile event-and-data driven design methodology for decisional Big Data projects
16 references·2 citing·48 second hop
DECIDE: An Agile event-and-data driven design methodology for decisional Big Data projects (2020)DECIDE: An Agile event-and-data driven de…Management challenges in creating value from business analytics (2017)Management challenges in crea…2017 IEEE International Conference on Big Data (Big Data) (2017)2017 IEEE International Confe…The need for new processes, methodologies and tools to support big data teams and improve big data project effectiveness (2015)The need for new processes, m…Data Science and its Relationship to Big Data and Data-Driven Decision Making (2013)Data Science and its Relation…Towards business intelligence systems success: Effects of maturity and culture on analytical decision making (2012)Towards business intelligence…Designing data governance (2009)Designing data governanceA Survey of Multidimensional Modeling Methodologies (2009)A Survey of Multidimensional …A Design Science Research Methodology for Information Systems Research (2007)A Design Science Research Met…Beyond data warehousing (2004)Beyond data warehousingA method for demand-driven information requirements analysis in data warehousing projects (2003)A method for demand-driven in…Designing data marts for data warehouses (2001)Designing data marts for data…From enterprise models to dimensional models: a methodology for data warehouse and data mart design. (2000)From enterprise models to dim…Conceptual Data Warehouse Design (2000)Conceptual Data Warehouse Des…The Data Warehouse Lifecycle Toolkit : Expert Methods for Designing, Developing, and Deploying Data Warehouses (1998)The Data Warehouse Lifecycle …Advances in Database Technology — EDBT'98 (1998)Advances in Database Technolo…A methodological framework for data warehouse design (1998)A methodological framework fo…Enhancing big data analytics deployment: uncovering stakeholder dynamics and balancing salience in project roles (2024)Enhancing big data analytics …From Big Data Technologies to Big Data Benefits (2023)From Big Data Technologies to…Research problems in data warehousing (1995)An overview of data warehousing and OLAP technology (1997)Goal-oriented requirement analysis for data warehouse design (2005)A UML-based data warehouse design method (2006)GRAnD: A goal-oriented approach to requirement analysis in data warehouses (2007)Building a Data Warehouse (2008)Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? 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References

  • 2007A Design Science Research Methodology for Information Systems Research7,798 cited
  • 2013Data Science and its Relationship to Big Data and Data-Driven Decision Making1,666 cited
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  • 2000From enterprise models to dimensional models: a methodology for data warehouse and data mart design.223 cited
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  • 2000Conceptual Data Warehouse Design174 cited
  • 2003A method for demand-driven information requirements analysis in data warehousing projects173 cited
  • 1998Advances in Database Technology — EDBT'98161 cited
  • 2009A Survey of Multidimensional Modeling Methodologies

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121 cited
  • 2015The need for new processes, methodologies and tools to support big data teams and improve big data project effectiveness109 cited
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    • 2023From Big Data Technologies to Big Data Benefits9 cited
    • 2024Enhancing big data analytics deployment: uncovering stakeholder dynamics and balancing salience in project roles8 cited