Data Quality Workbench
Intelligent control of data quality processes for existing customer and prospect data.
Insufficient data quality is a frequent companion in everyday business. What do you do if data quality problems have already become embedded in the customer or prospect database due to inadequate processes or tools? Then it is necessary to optimize mass data in a suitable manner.
But it doesn't always have to be the "sins" of the past why the customer or prospect dataset has to be processed completely or in large parts. Be it the redundancy-free execution of data integrations in the context of M&A, the restructuring of data in the context of migration projects, or the implementation of regular data maintenance and anti-aging to prevent the data stock from aging.
All of the above cases have a common challenge: mass data has to be processed, and there are usually rules for processing it that deviate from the "usual" day-to-day operations. Therefore, it usually makes sense to use special solutions with special customizing for this purpose.
The Uniserv Data Quality Workbench
Clean data is the ultimate
The Uniserv Data Quality Workbench is the "Swiss army knife" for mass processing of customer and prospect inventory data. It enables flexible data pipelines for data quality analyses and cleansing as well as data restructuring, consolidation and enhancement to be set up, tested and productive processing to be carried out.
The outstanding performance is particularly convincing - even with complex functions such as entity resolution or identity resolution and even with processing volumes of tens of millions of master records. The processing of the data pipelines can be performed manually as well as highly automated.
"The Data Quality Workbench is
the "Swiss army knife
for the mass processing
of customer and prospect data."
High-quality data from customers and business partners is indisputably a key factor for business success. If the data is up-to-date, complete, correct and unambiguous, the customer data processes work properly, personalized marketing campaigns can be run and customers can be individually accompanied along their customer journey, to name just a few examples. It doesn't matter whether it's a matter of data cleansing in legacy systems, in connection with migration projects, master data, risk management or compliance. Also and especially in the realization of customer orientation and retention projects, cleansed data is of great importance. The Data Quality Workbench from Uniserv creates optimum conditions here with regard to the topicality and reliability of data. And thus for their usability.
