How to Gain a Crisis Advantage with Real-Time Information

To reduce the impact of an unfolding crisis, companies need a clear, accurate and early line of sight into emerging risks. Leaders can then act with confidence and seize opportunities to preserve brand reputation while driving operational excellence. To demonstrate how real-time information can help companies gain advanced warn
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A Matter of Urgency: Using Data and AI to Drive Acquisition and Engagement

Fewer patients, preventative screenings, and primary care visits. Lower revenues. Worsening population health outcomes. The healthcare industry is facing serious challenges to its business model as consumer behavior shifts to other ways to meet their healthcare needs or a complete failure to seek care until conditions become acute. The need to meet consumers where they are and engage with them on their terms has never been more urgent.
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Building the Road Map for Real-Time Data and Analytics

As organizations strive to be more competitive, they often need real-time insights; no one wants to make decisions based on stale data. TDWI research indicates that real-time data collection is already in the mainstream. Some use cases include inventory management, fulfillment, supply chain, and logistics in which retailers must be able to assess product availability and consumer demand in real time. Forward-looking organizations also want to enrich real-time data with other data types to provide even better analytics.
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How Data Governance Helped Genworth Financial to See Data as an Asset

One of the biggest misunderstandings about data governance? An assumption that you need data governance only because you’re working with inherently low-quality or low-value data. The data governance team at Genworth Financial focused on changing the way the organization thinks about governance in order to improve how it captures, stores, transforms, analyzes, and presents data—which in turn unlocked their data’s full value.
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Strategic Imperative – The Enterprise Data Model


With today’s increasingly complex data ecosystems, the Enterprise Data Model (EDM) is a strategic imperative that every organization should adopt. An Enterprise Data Model provides context and consistency for all organizational data assets, as well as a classification framework for data governance. Enterprise modeling is also totally consistent with agile workflows, evolving incrementally to keep pace with changing organizational factors. In this session, IDERA’s Ron Huizenga will discuss the increasing importance of the EDM, how it serves as a framework for all enterprise data assets, and provides a foundation for data governance.
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