Data plays a key role in many company areas, such as sales, marketing and finance. To get the best out of the data, it must be maintained, protected and monitored over its entire life cycle. Data quality is a core element of Uniserv company philosophy and the product offers it makes. Our customised solutions make your customer master data the success factor of your company.
The Data Quality Service Hub ensures high level customer data quality at every location in your company – and at international level. We offer you correction of your address information according to international standards and based on first-class reference data. We also check email addresses, telephone numbers and bank data at different levels. If you have redundant items in your data, we can flexibly search for duplicates according to your business rules. These items found can be mostly consolidated automatically based on prescribed rules, or sorted for manual reprocessing.
By enriching your master data with business relevant information, its value can increase, e.g., by supplementing addresses with geo-coordinates or with branch keys. Data quality solutions can be incorporated into your business processes either in real time, or as batch processing, and according to your individual needs. You can also use a wide range of data quality functions flexibly in the cloud. Uniserv gives you the high quality data basis which answers your demands entirely. But this not only means an increase in the efficiency of your employees; it also means that your company processes run more smoothly, that you can act and react more successfully in the market, and that the results will soon show a positive effect on your company figures. In other words: Better Data = Better Business.
Learn more about the Uniserv data quality tools:
Data Analyzer, Data Cleansing, Data Protection and Data Governance.
Similar symptoms of poor data quality often arise during discussions with our customers and employees from different specialist departments. These symptoms allow reference points for concrete data quality initiatives to be established and initial ideas for catalogue of measures to be created.