Tag Archives: dqs

Airlines. Centralized Customer File.

Building and implementation of Central Index of Contractors – integration of sale systems data, customer service and CRM.   „We have a wealth of information about our clients but... we don't know much about them. Sometimes it is hard for me to tell which data are about which customer.” This in not a rare case…
Continue reading

Utilities. Customer data cleansing.

  With over six million customer records, manual verification was out of the question, all the more so given that manual data correction does not guarantee full correctness. It was necessary to develop automatic data quality improvement mechanisms. One of the main challenges faced by our Client, a leading electricity distributor in Poland, in introducing…
Continue reading

Banking. Data cleansing.

  Sanmargar completed a project involving comprehensive and automatic improvement of the quality of data of the Bank’s customers, including master data and identification data, ID document data, address and phone details, data on links and relations between customers, and classification data. The number of bank customer data records involved in this project was more…
Continue reading

Energy. Customer data deduplication.

More than six million customers in databases, but only three million real customers? How not to migrate the whole burden of duplicate or multiple customer records to a newly implemented system? How to spot different electricity supply points corresponding in fact to one and the same electricity customer and payer? And finally, how to ensure…
Continue reading

Media. Central customer data repository.

A project involving the development and implementation of a central customer data repository at a media concern. Sanmargar, as a subcontractor, was responsible for the cleansing of customer data and the creation and loading of a customer reference database for the purpose of the application.
Continue reading

Retail. Data cleansing.

Nearly 200 retail stores all over the country, operating under the franchise model, with separate cash register systems and separate product definitions in those systems, give rise to millions of sales records comprising ambiguous data on a daily basis. How to effectively analyze and report sales for the entire chain in these circumstances? Semantic methods…
Continue reading