Harness Real-time Public Information to Improve Active Shooter Response

Corporate security teams hope never to respond to an active shooter situation. But given today’s realities, companies spend a great deal of time developing guidelines, holding training sessions, and carrying out drills to ensure that their staff will be prepared in case an active shooter event occurs. Protocols in place for many
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OTHER ON-DEMAND WEBINARS

Lynx: A FAIR-fuelled Reference Data Integration & Look up Service at Roche

Roche, as a leading biopharmaceutical company and member of the Pistoia Alliance, has a diverse and distributed ecosystem of platforms to manage reference data standards used at different parts of the organization. These diverse reference data standards include ontologies and vocabularies to capture specifics of the research environment and also to describe how clinical trial data are collected, tabulated, analyzed, and finally submitted to regulatory authorities. In the context of the EDIS program, Roche has bridged these parts to improve reverse translation from studies into research and also embraced FAIR to emphasize machine-actionability and data-driven processes.
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Why BI Programs Fail to Scale: The Data Decision Gap

The global investment in digital transformation estimated to exceed $10 trillion over the next five years. Despite the tremendous resources going towards this cause, studies show that up to 70% of these initiatives will not achieve their stated goal. What does it take to win?
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Sprint or Marathon? Going the distance with data center maintenance

Navigating the course of data center management comes with a multitude of obstacles. Most IT professionals must balance maximizing uptime, improving security, optimizing operations and meeting budget realities. In the case of data center maintenance, what is the best route to take after initial warranty support expires? Uptime a
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The Rise of Data Mesh and Data Fabric Architectures

As businesses strive to advance digital transformation efforts, legacy architectures can be a significant obstacle to enabling the agility required to succeed in today's ever-changing data landscape. Many enterprises struggle with scaling the delivery of data and analytics to accommodate the growing array of data domains, users, and use cases. As a result, data mesh and data fabric architectures are on the rise with the aim of abstracting data management complexity, increasing data availability, and fostering greater collaboration.
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