Many data modelers are discovering that their traditional data modeling processes no longer align with the demands of modern software development methods, such as agile or scrum. As these methods have become the standard in enterprise organizations, data professionals often struggle to contribute effectively to software projects.
This struggle frequently results in the exclusion of data products and services from critical project work.
Traditional data modeling approaches tend to be rigid and unable to adapt quickly to the iterative, flexible nature of agile environments. As a result, data professionals are left behind in the evolution of software development, limiting their ability to provide real-time insights and support.
To address these challenges, data modelers must tailor their approaches to better support agile and scrum methodologies. By adopting more flexible and collaborative data modeling workflows, data professionals can bridge the gap between data and development teams. This shift enables seamless integration into agile projects, ensuring the delivery of high-value data insights.
Karen López’s 11-page whitepaper, “Is Your Data Modeling Workflow Agile or Fragile?”, provides a comprehensive guide on modern data modeling. It explores key components of agile data modeling processes, challenges faced by data modelers in agile environments, and practical tips for implementing an agile, rather than fragile, data modeling workflow.
