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Research and Best Practices for Modern Data Architecture

June 11, 2020

Prerequisite: None

Philip Russom, Ph.D.

Senior Research Director


Phillip Russom, TDWI’s Senior Research Director for Data Management, will address complex modern requirements for hybrid data and its business use.

One of the strongest trends in data architecture today is toward environments consisting of numerous data platforms where data is physically distributed across multiple database servers, file systems, and storage subsystems at multiple locations. Any of these may be on premises, in the cloud, or in a combination of the two.

The complexity that results from the number of systems involved is daunting. Yet it is multiplied by an extreme diversity of platform types, including older relational databases and other legacies, new relational cloud databases, NoSQL platforms, open source, and tools for data integration, analytics, and stream processing.

Furthermore, data is evolving into greater diversity (more data types, sources, schemas, and latencies) and higher volumes and speeds (big data, real-time streams). At the same time, user organizations are diversifying how they use data for business value, typically via advanced analytics, customer views, operationalizing IoT, and data shared across business units. Given the highly diverse requirements of modern data and its use cases, many users satisfy these requirements by spinning up even more data platforms and tools, thereby increasing the complexity of modern data architectures.

This presentation will draw from TDWI Research reports to describe the trends and best practices of modern data architectures, with a focus on hybrid data architectures and data migrations to the cloud.

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