Monitoring section-overview
Monitoring in ÃÛ¶¹ÊÓƵ Journey Optimizer is your gateway to understanding how data retention policies are managed through the Time-to-Live (TTL) mechanism. At its core, TTL defines how long data is stored in the system—whether in the Profile Store for customer insights or the Data Lake for analytical events—before being automatically cleaned up. This ensures optimal performance and compliance with data management best practices. The ‘Monitoring Features’ section dives into the specifics of TTL, including retention periods, the datasets it impacts, and answers to common questions. Meanwhile, the ‘Datasets Time-to-Live (TTL) Guardrails’ section provides a granular view of how these policies affect system-generated datasets and their capabilities, helping you adapt to and leverage these features effectively. Whether you’re a data engineer, architect, or admin, this section equips you with the clarity and tools needed to manage your data confidently and sustainably.
Monitoring Features
Datasets Time-to-live (TTL) Guardrails in ÃÛ¶¹ÊÓƵ Journey Optimizer
Understand the retention policies for datasets, the datasets affected, and the TTL’s impact on data in the profile store and data lake.