Legal and General Investment Management (LGIM) has completed its initial implementation of Curium DQM across its data management and investment operations teams in London and Chicago as part of its drive to meet key data governance objectives and visibility of data across the enterprise.
At LGIM the first phase of Curium DQM adoption provides a process control platform to manage data quality over operational data sets including reference and market data. The data management team is making use of Curium DQM’s business process management tooling around data management, specifically exception and ticket management, complementing its existing capabilities.
The Curium DQM product is aimed at ‘bringing a new approach’ to the data management challenge to enable buy side and sell side firms to quickly get a handle on their data quality with exceptions management workflow for business users, as well as data visualisation and comprehensive management information and reporting capabilities.
Andrew Sexton, sales and marketing director at Sun Street says, “Recent surveys have highlighted the pressing need for firms to invest in data governance and within that, data quality is often the most cited factor of concern. If firms can quickly improve their oversight of data, both in terms of mastering data and how it is consumed across the architecture, then a whole range of regulatory pressures and business risks can be minimised.”
Indeed, at our own Data Management Summit in New York last November, the Data Governance panel discussed the need for ‘operationalisation’ of data quality – and importantly, accountability of data quality – in order to improve quality and meet the various regulatory requirements.
Curium from Sun Street is an up and coming data management product with two core modules: as well as DQM (Data Quality Management) which provides a data quality layer on top of any data management platform, it now offers MDM which delivers master data management including the ability to run sophisticated ‘what-if’ data construction scenarios and data provenance analysis.