About the Webinar
This presentation explores the critical role of data modeling and data architecture as foundational disciplines for modern enterprises. It argues that data representation is the essence of programming and that a clear, documented data model acts as the “digital blueprint” for an organization, enabling a common understanding among business users, technical personnel, and systems.
The core message is that suboptimal data practices accumulate “data debt” and lead to complex, brittle systems. The presentation illustrates how moving from chaotic, point-to-point integration to a structured “Spoke and Hub” approach, centered on a robust data model, is essential for reducing complexity and cost. It emphasizes that data models are a stable, reusable component of any system and are the most reliable means of conveying the enormous amount of information required for effective data management.
The webinar highlights the need for a collaborative approach to data modeling, including both forward engineering (goal: building new systems) and reverse engineering (goal: understanding existing ones). By understanding what data exists, organizations can avoid common errors, reduce risk, and leverage their data to build stable business models and support strategic goals.
About the Speakers
Peter Aiken, Ph.D. is an acknowledged Data Management authority, an associate professor at Virginia Commonwealth University, president of DAMA International, and associate director of the MIT International Society of Chief Data Officers. For more than 40 years, Peter has learned from working with hundreds of Data Management practices in more than 30 countries. Among his 13 books are the first on making the case for data leadership (CDOs), the first focusing on data monetization and modern strategic data thinking, and the first to objectively specify what it means to be data-literate. International recognition has resulted from these and a (pre-Covid-19) intensive worldwide events schedule. Peter also hosts the longest-running Data Management webinar series on dataversity.net. Before Google, before data was big, and before Data Science, Peter founded several organizations that have helped more than 200 businesses leverage data – specific savings have been measured at more than $1.5 billion. His latest venture is Anything Awesome.
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