The state of data quality arts in (technical) service reporting

Abstract

Service Level Management (SLM) in IT Service Management (ITSM) contains Technical Service Reports (TSRs) to report Service Quality (SQ) based on the Service Level Agreement (SLA). However, producing TSRs for a large enterprise has Data Quality (DQ) challenges. The source of technical metrics in TSRs comes from large, unverified and non-normalized system-generated events and logs in a large enterprise environment. Moreover, configuration items and service information meta-data that are essential for producing these SLM reports are facing DQ problems. These challenges lead to low reports' Data Quality (DQ) that destroy customer's trust and management visibility, which leads to financial penalties and SQ issues. In order to improve the TSRs' DQ and consequently improving the SQ and reducing the risks of financial penalties, researchers need to know the limitations and definitions of DQ for TSRs, and this is not feasible, except for having a comprehensive overview of DQ dimensions and its processes. This paper provides a statement on the situation of the DQ in existing literature by having eyes on technical service reporting issues.