An emerging markets mobile telecommunications operator, and one of the most valuable brands in Africa, at the forefront of technological and digital changes, offering voice, data and digital services to retail customers in the 22 countries.
The Business Challenge
Telecom operators around the world struggle with the challenges of maintaining their Data Quality (DQ) due to the sheer complexity of the systems and functions involved, as well as the volume of data to be managed. Poor data quality leads to large revenue leakage and process failures.
The solution consists of a customised and easy deployable Data Quality Framework. Although the solution can be connected to all data components in the data warehouse, it was initially developed to improve the quality of the data feeding the various machine learning models that had been developed for the client. The DQ framework supports complex weighted algorithms used to determine acceptance thresholds. It may cover all areas of data qualities. Business rules are configured to interpret the results of the DQ measures against the subject areas and send alerts when thresholds are crossed. Data quality executive dashboard were also developed. This provides an opportunity to take corrective action in a timely manner to mitigate the impact on downstream systems or data sources, improving operational processes and over time reducing time spent re-running tasks.
The Value Proposition
The Data Quality Framework addresses the organization’s Data Governance requirements with specific focus on Data Quality management. It provides a mean to measure, monitor, control, and report data quality issues relating to the data warehouse environment, thereby giving a solid foundation on which to develop further an information quality strategy
No posts were found.