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Nina Showell
Principal Analyst
Gartner
Speaker Topics
- Data Integration
- Data Architectures (inc. Data Fabric, Data Lakes, Data Warehouse)
- Operating Model
- Data Products
- Cost Optimization
Speaker Bio
Nina Showell is a Principal Analyst on the Data Management team. Mrs. Showell's area of research is data integration (ETL, ELT, data virtualization, data replication, streaming), with additional interests in metadata, data fabric, data mesh, data products, federated data management, and self-service data & analytics.
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Sessions
Monday, 28 April, 2025 11:00 AM - 11:20 AM BRT
Magic Quadrant for Data Integration Tools
Nina Showell,
Principal Analyst, Gartner
Data integration tools help organizations access, process, move and transform data. They support use cases like data engineering, modern data architecture, less-technical/business user support, and operational data integration. In this session, we'll present the latest Magic Quadrant for Data Integration Tools, discussing vendors and technologies to help you choose the best tool for your needs.
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Monday, 28 April, 2025 04:00 PM - 04:30 PM BRT
Lakehouse: One Small Step for a Data Architect, One Giant Leap for the Organization
Nina Showell,
Principal Analyst, Gartner
Lakehouse has become a cornerstone in managing large and heterogeneous data by providing capabilities that simplify organizational data architecture, unify data assets, and help streamline, harmonize, and enhance data processes, operations and governance. Lakehouse provides high value to the organization, reduces technical debt, and prepares the organization for new frontiers like AI.
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Tuesday, 29 April, 2025 04:30 PM - 05:00 PM BRT
From Strategy to Execution: Aligning Modern Data Architectures With Your Operating Model
Nina Showell,
Principal Analyst, Gartner
This presentation will explore aligning modern data architectures and delivery styles (data products, data fabric and data mesh) with your organization's operating model. We'll explain operating models and their importance, then discuss the benefits and challenges of each data delivery approach. You'll learn to align your operating model with architectural choices to improve data management.
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