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Adam Ronthal
VP Analyst
Gartner
Speaker Topics
- Metadata Management
- Data Architectures (inc. Data Fabric, Data Lakes, Data Warehouse)
- Data and Analytics Governance (any data, analytics, or AI)
- Overall Data and Analytics Strategy
- Cost Optimization
Speaker Bio
Adam Ronthal is a Research VP in Gartner's Data and Analytics group covering data management with a primary focus on database management systems, technologies and strategies. Mr. Ronthal's areas of specialization include data ecosystems, analytic and operational databases, cloud, financial governance for cloud and FinOps for D&A. Mr. Ronthal joined Gartner in January 2015 and is based in Toronto, Canada.
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Sessions
Monday, 12 May, 2025 01:00 PM - 01:45 PM BST
Roundtable: How Can D&A Leaders Mitigate the Risk of Operating in an Uncertain Geopolitical Landscape
Adam Ronthal,
VP Analyst, Gartner
Data and analytics leaders must operate within the realities of the geopolitical impacts that we now face. These include an increased focus on contingency planning for diverse vendor selection, avoid reliance on products or technologies that may be subject to trade policies or other restrictions and confronting increased costs.
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Tuesday, 13 May, 2025 09:00 AM - 09:30 AM BST
Simplify the Complex Data Management Infrastructure with Data Ecosystems
Adam Ronthal,
VP Analyst, Gartner
Data ecosystems, built on data fabric design and infused with AI, promise an integrated, cost effective, and operationally simple approach to varied data management challenges. However, they don't yet always deliver on that promise. This research explores the maturity of various ecosystem components and provides a guide for D&A leaders and others looking to invest in data foundations for competitive differentiation.
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Wednesday, 14 May, 2025 10:30 AM - 11:00 AM BST
Searching for the Data Management Theory of Everything
Adam Ronthal,
VP Analyst, Gartner
For over a decade, we have sought a holistic, unifying theory of data management. This presentation documents the quest, and touches on the data and analytics infrastructure model (DAIM), metadata, data fabric, data ecosystems, and FinOps. Each of these is required and together they address everything from infrastructure to AI to strategy communications.
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