sav

Savills Estate Agents

The task for DQ Global was to show Savills how they could create a generic solution to identify duplicates at company, contact and address levels, create a master record into which any colliding One-to-One data could be merged, then re-assign all One-to-Many linked records to create the “Perfect Customer Record”; when all three of their Pivotal systems were configured differently.

marcus-evans

Marcus Evans

Marcus Evans needed to ensure that the large selections of client data records that are used for promoting customer events could be exported fast, efficiently and free of duplicates from the in house database for use in marketing campaigns. Poor quality data could potentially damage the Marcus Evans brand, waste budget on undeliverable communications and create additional data re-work for employees.

lewisham

Lewisham Hospital

With approximately 150 ‘new patient’ registrations each day to be compared against the 930,000 existing records in the Lewisham Hospital NHS Trust database, the search for duplicate records was a time-consuming manual task, taking more than half a day. At one stage there was a six month backlog. Using Match, searching for new patient records in the database takes about 10 minutes. Every day, around 10-15 records are identified where the patient has an existing medical record at the hospital.


harvey-nichols

Harvey Nichols

Harvey Nichols wanted to merge data from seven disparate data sources into a Pivotal/Market First CRM system to create a single shopper view for marketing and e-marketing purposes. Once they had attained a single customer view, the data then had to be kept in sync thereafter, involving constant cross-matching, updating and point of entry validation. DQ Global also supplied Match and Authentic8 software to enable Harvey Nichols to continue to maintain the accuracy of their data.

ww

WHIS

The project at WHIS was part of a national research initiative on the Electronic Health Record (EHR). Wirral was tasked to develop the electronic record register for cancer patients. The data quality issue arose from trying to identify non identically matching patient records across multiple and different organisations to create a common holistic view of the cancer patient’s records. DQ Toolkit allowed WHIS to embed data formatting, standardisation and matching capabilities right into their patient record management application, enabling WHIS to identify duplicate patient records with very high levels of confidence.