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            Data Drift in High-Frequency Data Graph Refreshes

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            Data Drift in High-Frequency Data Graph Refreshes

            When you schedule a data graph to refresh more frequently than once per day, you can experience data drift. Data drift occurs when rapid refresh cycles don’t fully capture or reconcile updates from the source system, causing temporary inconsistencies in the data graph.

            Required Editions

            Available in: All Editions supported by Data 360. See Data 360 edition availability.

            A full refresh automatically runs once every 24 hours and corrects any drift that occurs during more frequent refresh cycles.

            What Causes Data Drift

            Data drift can occur when the data graph is refreshed multiple times before a full refresh completes. Common causes include:

            • Partial Updates: If records in the source system change several times within a day, not all updates appear in the data graph until the full refresh runs.

            • Deleted or Modified Records: Records that are deleted or changed in the source remain in the data graph until the next full refresh reconciles them.

            • Complex Relationships:When related data or join keys are updated, mismatched or duplicate nodes can appear in the graph until the full refresh reprocesses all data.

            • Hierarchical Dependencies: Drift can also occur when updates arrive for deeper-level nodes before their parent nodes exist in the system. In such cases, child records temporarily appear as unmatched or missing relationships until the parent nodes are processed during the full refresh.

            How Data Drift Is Corrected

            A scheduled daily full refresh reprocesses all data from the source and realigns the graph with the most recent state of your data. This process removes any inconsistencies, duplicates, or outdated records that appear during high-frequency refresh cycles. As a best practice, use higher-frequency refreshes only when near-real-time data is required and temporary inconsistencies are acceptable.

             
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