Expert Panel: Real-Time Analytics Use Cases and Architectures
Webinar Speaker: James Kobielus, Senior Research Director for Data Management
Date: Monday, December 9, 2024
Time: 9:00 a.m. PT / 12:00 p.m. ET
Real-time analytics can deliver the fast insights and immediate responses that enable business success. When enterprises optimize their IT infrastructures to support end-to-end low latencies, they can deliver real-time data-driven insights into back-office operations, multichannel customer experiences, and strategic decisions at every level of the organization.
Every industry has mission-critical use cases that require real-time analytics. One of these principal applications is customer engagement optimization, which leverages real-time customer insights to deliver personalized experiences, product recommendations, and targeted offers in real time. Another is fraud detection, which uses real-time analytics to flag suspicious activities immediately and shut down fraudulent transactions before they can happen. Yet another is supply chain optimization, when enterprises leverage real-time analytics to predictively optimize manufacturing, inventories, shipping, and other activities to keep pace with demand and prevent possible disruptions.
In this expert panel, TDWI senior research director James Kobielus will discuss the chief enterprise use cases for real-time analytics and the principal architectural considerations for data, analytics, and IT professionals seeking to optimize their infrastructures for these applications. He will be joined by industry experts in a panel in which they will discuss:
- What is the mission-critical value for real-time analytics in modern business and what are the top use cases?
- How do real-time analytics requirements vary by industry?
- How can organizations support real-time and batch processing side-by-side in their data analytics architectures?
- What are the principal uses of change data capture, stream processing, and in-memory data stores within a low-latency analytics architecture?
- How can real-time analytics support comprehensive observability over enterprise data pipelines?
- How can enterprise investments in real-time analytics platforms support development of generative AI and other advanced data-driven applications?
- What are the best practices for migrating an enterprise’s legacy batch data platforms, tools, and applications to a real-time, low-latency platform?
Date: December 9, 2024
Time: 9:00 am PT
James Kobielus