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Ten Mistakes to Avoid In Migrating Data and Analytics Platforms to Cloud Infrastructure
TDWI Member Exclusive

September 13, 2019

By Coy W. Yonce III

Data and analytics platforms are a lifeline for many organizations as they seek to create, expand, and improve on more efficient business processes. Analytics is being embedded into every facet of an organization and is used to drive every decision the organization makes. The data being fed into these analytics platforms is coming from more varied sources in the form of highly structured data, highly unstructured data, and data that's somewhere in between. Being able to process all the data coming into an organization within analytics that is easy to consume, easy to understand, and easy to act on means creating analytics environments that can be deployed quickly and scaled instantly.

This Ten Mistakes to Avoid focuses on helping organizations make the transition from on-premises data and analytics platforms to cloud-based deployments more efficiently and thoughtfully. The tips offered here will provide guidance for the types of decisions you will need to consider, the options available as part of those decisions, and concrete examples of the net impact to your organization.


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