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For one agricultural seed customer, their established pipeline from harvest data ingest to end-user visualization had taken years to assemble and still did not achieve the insight desired.
Their pipeline involved highly complex transforms, required multiple large teams to maintain, and was unable to process petabytes of harvest data to produce a worldwide heat map. These are issues that many organizations—regardless of industry—can relate to.
Browse this case study to discover how this customer achieved their worldwide heat map goals after building a more scalable data pipeline—and to apply their successes in your organization.