Datanomic adds Bragg to sales team, upgrades dn:Director

Source: Datanomic

Enterprise data management specialist Datanomic has announced the appointment of Peter Bragg to its commercial team, as it releases the latest version of its dn:Director solution.

The latest appointment follows increased demand for Datanomic’s dn:Director software globally. Peter will be responsible for Datanomic’s business in the Central Government, Pharmaceutical and Travel/Transport/Logistics sectors.

Peter, a seasoned IT professional with over 20 years experience of new business solution sales, has spent the last five years selling into a number of sectors including financial services. A proven professional with a track record of over-performance, Peter started his IT career at IBM. He has since held senior roles and until recently was a Senior Account at eGain Communications. Previously a Co-Founder and Director of solution reseller, Ovidium, Peter has also been the Country Manager of Mindjet UK and a New Business Development Manager at Remedy.

“Peter came to our attention because of his strong execution skills, proven consultative selling experience and his ability to spearhead business development into growing sectors,” said Dr Jonathan Pell, CEO, Datanomic Ltd. “We expect 2009 will be another successful year for Datanomic as we continue to expand our market share. We look forward to working with Peter.”

Datanomic recently announced the general availability of dn:Director 7.1, featuring tailored user interfaces for collaborative working that automatically generate customised warnings around data rules, as well as the ability to take over matching from third party products without losing decision history.

dn:Director 7.1 includes significant architectural enhancements to support role-based tailored UIs to support the needs of different users, such as Data Analysts, Data Stewards, Executives and Match Reviewers. Email notification capabilities have been built in to the product allowing customised warnings and error messages to be triggered at any point in processing.

Datanomic has also enhanced the integration capabilities of dn:Director 7.1. Decisions from dn:Match, or other matching products, can be imported to ensure there is no loss of manual work or audit trail when migrating to dn:Director matching. The new decision import capability also allows customers to conduct external reviews of matching results, with decisions re-imported into the matching process. New configurable Time Zone options are available to ensure full compatibility for geographically distributed users.

“We are committed to the ongoing development of our industry leading, fit-for-purpose data quality management platform, dn:Director, which enables organisations to better understand their data issues, and clean, manage and maintain a meaningful level of data quality,” said Dr Jonathan Pell, CEO of Datanomic. “dn:Director 7.1 provides role based access with user interfaces that are specifically tailored for administrators, analysts, data stewards, reviewers and executives to promote a collaborative approach to enterprise data quality projects. We have also added a solution building capability which allows the integration of documentation with custom built processors for ease of use. Our multi-national customers will also benefit from dn:Director’s improved multi-language discovery, and time zone handling for geographically distributed use. The dn:Director platform enables users to have full control over their data enhancement processes to ensure their data is fit for business use.”

Described by industry analysts as “arguably the most flexible data quality product”, Datanomic’s dn:Director provides a single, unified platform that enables both business and IT personnel, such as data stewards, business analysts and owners of data, to identify and rectify compromised data which can place operations at risk. As a single product that encompasses profiling, analysis, matching and transformation, dn:Director enables better understanding, improvement, protection and control of data quality for all types of structured and non-structured, real-time and non-real time information.

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