An organization is just getting started with Data 360 and wants to demonstrate quick wins in order to build momentum for broader adoption. Which business outcome should the organization prioritize?
A.
Consolidating all partner and supply chain data into a single master management hub
B.
Implementing a global data lineage system to calculate data quality scores and create audit reports for compliance teams across all business units
C.
Building a predictive platform to update dynamic segments every 30 seconds
D.
Improving customer service resolution times by giving support agents a 360-degree view
The core Data 360 principle is harmonization: bring data from multiple systems into a governed model that business teams can use consistently. Improving customer service resolution times by giving support agents a 360-degree view is the strongest answer because Data 360 is designed to unify, harmonize, and activate customer and business data across systems. The platform is not merely a dashboard, archive, or point solution. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.
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