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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Spotlight

OTHER ON-DEMAND WEBINARS

Real-time Machine Learning: Architecture and Challenges

Fresh data beats stale data for machine learning applications. This on demand webinar discusses the value of fresh data as well as different types of architecture and challenges of online prediction, it will also cover the tradeoffs between latency, staleness, and cost.
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Under The Hood Of A Shard-Per-Core Database Architecture

Most databases are based on architectures that pre-date advances to modern hardware. This results in performance issues, the need to overprovision, and a high total cost of ownership. In this webinar, we will discuss the advances to modern server technology and take a deep dive into ScyllaDB’s shard-per-core architecture and our asynchronous engine, the Seastar framework.
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Master Data Management–Aligning Data, Process, and Governance

dataversity

Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM “right” requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the “sweet spot” between technology, design, process, and people for your MDM initiative.
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Moving from centralized data platform to a federated data mesh

In this webinar, we will cover the pros and cons of building a centralized data lake vs federated data mesh. Traditionally data warehouses are built on the premise of centralized data. This requires team, process and tool alignment which adds significant complexity and layers of process. Oftentimes the internal conflicts lead to subpar data management and quickly fragments to siloed data processing and insights. We will provide our unbiased view on building federated data mesh and the benefits of building an operational metrics layer.
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