DIM_SLA_CONFIGURATION
Updated
DIM_SLA_CONFIGURATION is a dimension table that stores configuration and metadata for Service Level Agreement (SLA) definitions, including channel-wise SLA objectives, working-hours applicability, ownership details, and lifecycle timestamps. It supports monitoring, evaluation, and reporting of SLA performance across different channels and configurations. Below are some of the scenarios where this Report is beneficial:
SLA Performance and Compliance Monitoring: Analyze SLA configurations across channels to measure response and resolution performance, identify breaches, and ensure compliance with service commitments.
Channel-Specific Service Optimization: Compare SLA objectives and outcomes across channels to identify areas for improvement and optimize customer service operations.
SLA Configuration Governance and Auditing: Track SLA ownership, working-hours applicability, and configuration changes to maintain consistency, support audits, and ensure adherence to service policies.
Field Mapping/ Glossary
The report will include the following information:
Expected Name | Definition | Data Type | Nullable & Default Value | PII Field | Unique Key |
SLA_CONFIG_ID | Unique identifier of the SLA configuration | VARCHAR | No | No | Yes |
LAST_MODIFIED_AGENT_ID | Identifier of the agent or system that last modified the SLA configuration | VARCHAR | No | No | No |
OWNER_AGENT_ID | Identifier of the agent who owns or is responsible for the SLA configuration | VARCHAR | No | No | No |
SLA_CONFIG_TYPE | Type or category of SLA configuration (e.g., Global, Channel-specific, Queue-specific) Sample Values: PARTNER, WORK_QUEUE_USER_MAPPING |
VARCHAR |
No |
No |
No |
Intended Use and Prohibited Uses
DataStream is intended solely to support operational efficiency, service delivery, business intelligence, and process optimisation. The product is not designed or intended for employee monitoring, workplace surveillance, performance evaluation, profiling of individuals, or making decisions that materially affect an individual's employment, rights, opportunities, or access to services.
DataStream does not process biometric data for the purpose of identifying individuals and does not perform emotion recognition, affect detection, or emotion inference in the workplace.
Customers must not use DataStream in a manner inconsistent with these intended purposes and remain responsible for ensuring compliance with applicable legal and regulatory requirements as well as with Sprinklr's Acceptable Use Policy.