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RESEARCH & RESOURCES

Coffee Talk: Modernization Through Cloud Data Migration

Webinar Speaker: James Kobielus, Senior Research Director, Data Management

Date: Wednesday, September 28, 2022

Time: 12:00 p.m. PT, 3:00 p.m. ET

Join us live to receive a $5 Starbucks gift card!*

This Coffee Talk is part of the TDWI Modernization Series, which includes a corresponding playbook of the key takeaways to help you take action on the best practices shared. Sign up for the Coffee Talk and pre-save your analyst report – we will send it to you when published  in October!

Modern data runs in cloud-native environments. Migration of legacy on-premises data to the cloud is becoming necessary because enterprises are facing several critical pain points with their on-premises deployments, including siloed on-premises data stores that prevent unified roll up of data and analytics, limited technical support staff to manage on-premises data, and scalability constraints resulting from inflexible architectures of on-premises data platforms.

Join TDWI’s senior research director James Kobielus on this webinar, in which he will discuss the key steps for migrating legacy enterprise data and analytics platforms—including data integration pipelines and data warehouses—to the cloud. He will explore how, post migration, cloud-native data and analytics environments can be operationalized through such innovative features as automated data engineering pipelines, integrated data and model governance, and searchable data catalogs.

He will discuss how enterprises can:

  • Modernize both their data integration and data warehousing environments around cloud-native principles
  • Modularize the data integration and data warehousing assets for maximum reuse
  • Convert their legacy data integration and data warehousing assets with full fidelity
  • Automate their migration to modern data integration and data warehousing environments
  • Augment the skills, productivity, and teamwork of data integration and data warehousing professionals in order to fully operationalize the migrated data analytics assets

James Kobielus


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