Data Quality Management
Data quality in the Train Information System (TIS) is a crucial factor in ensuring the reliability of data that is also used by IMs and RUs to feed their own systems. Data extracted from the database is used to create reports through additional tools, such as Oracle Business Intelligence (OBI). Since TIS is fed by different national systems, data quality problems may occur at different stages:
- Delivery of incorrect data by legacy systems
- Incomplete data transferred from legacy systems to TIS
- Incompatible data provided by different legacy systems concerning the same train
- Incorrect data processing or data loss within TIS
- Incorrect data transfer to sub-systems (such as OBI)
- Incorrect data processing or data loss in sub-systems
To provide reliable information at all these stages data quality checks must be performed.
The Data Quality Working Group is composed of data quality experts tasked with the in-depth analysis of TIS data and relationships between these data. The working group analyses problems and forwards the resulting tasks/corrective actions to the responsible partner.
RNE has created a structured framework defining the different meanings of data quality as regards various different procedures (reports, evaluation, corrective actions, responsible partners, KPIs) and has published them in the TIS Data Quality Management Handbook.
Moreover, to highlight the importance of reliable data, especially for reporting purposes, the Data Quality Strategy for Reporting Purposes and specific follow-up projects to fulfill the strategic objectives are currently being defined and will start in the near future.