What is the difference between Data Governance and Data Stewardship?
Data governance and data stewardship are tightly related, but they are not the same thing.
Data governance and data stewardship are tightly related, but they are not the same thing.
Experts Rebekah Stickfort and Marisa Macho from Principal Financial Group and Infogix will be hosting a webinar on “How to Roll Out a Data Governance Program across Multiple Business Units.”
Due to the nature of the data that financial institutions process, a tightly controlled data management strategy is an absolute must for such organisations—not only to meet their business goals but also to ensure compliance with data-related regulations and keep their data safe and sound.
As much as digital transformation involves the use of technology, it is not purely about technology.
2020 has introduced numerous new challenges for data integration – including data migrations to the cloud, meeting personal data protection requirements and real time analytics. The rapid pace of change has left many Data Integration teams struggling to keep up.
Location intelligence and data enrichment help business leaders to make better decisions – from everything from site selection, to targeted marketing, risk management, routing, resource allocation and network optimisation
As much as digital transformation involves the use of technology, it is not purely about technology. It is about driving improved customer experiences and enhancing operational capabilities. What this requires, more than anything, is actionable business-driven intelligence, including location-based intelligence to help organisations better understand their customer.
Would you like to get a preview of the latest data governance, data quality, data catalogue, data lineage and metadata management solutions in action?
Address data is one of the most critical data resources available to businesses with an ecommerce function. Whether you’re a restaurant, a fashion retailer, or a bank, the need to understand location at the address level, and the risk of getting it wrong, has now been turbo charged in this fragile economic period.
Traditional master data management (MDM) projects have tended to be cumbersome, complex and never-ending. Although MDM purports many benefits, the reality is that projects have typically become centred on data integration, which makes these benefits difficult to realise.