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Become More Data-Driven by Evolving Analytics Workloads

CIO Business Intelligence

Data-driven organizations understand that data, when analyzed, is a strategic asset. It forms the basis for making informed decisions around product innovation, dynamic pricing, market expansion, and supply chain optimization. Just starting out with analytics? Find out more about Intel advanced analytics.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

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Your 5-Step Journey from Analytics to AI

CIO Business Intelligence

One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Just starting out with analytics?

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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO Business Intelligence

Blocking the move to a more AI-centric infrastructure, the survey noted, are concerns about cost and strategy plus overly complex existing data environments and infrastructure. Though experts agree on the difficulty of deploying new platforms across an enterprise, there are options for optimizing the value of AI and analytics projects. [2]

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