))
Rethinking Real-Time Analytics: Building the Foundation for Real-Time AI
Manage episode 460374258 series 2879792
Indhold leveret af EM360Tech. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af EM360Tech eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
In today’s data-driven world, real-time analytics has become a cornerstone for businesses seeking to make smarter, faster decisions. From enhancing user experiences to enabling continuous intelligence, the ability to process data in real-time is transforming industries. Yet, challenges such as legacy systems and the demand for innovative data management approaches persist.
This episode explores the evolution of real-time analytics and its crucial role in modern data processing. We delve into how technology is reshaping the way businesses interact with data and the importance of user-centric design in creating powerful data applications.
Joining Christina Stathopoulos, Founder of Dare to Data, is Rahul Rastogi, Chief Innovation Officer at SingleStore. Together, they discuss the necessity of real-time data in today’s fast-paced business environment, tackle the challenges organizations face in adapting to this shift, and highlight how data serves as the foundation for AI-driven innovation.
Don’t miss this insightful discussion packed with practical strategies and forward-looking ideas!
Key Takeaways
- Real-time analytics has evolved from a luxury to a necessity.
- Streaming technologies like Kafka and Spark have revolutionized data processing.
- Legacy systems are often monolithic and ill-suited for real-time analytics.
- Modern data platforms enable easier data management and integration.
- Continuous intelligence requires a solid analytics foundation.
- User experience is critical for the adoption of data applications.
- Organizations must treat data as a valuable asset.
- Data governance and quality are essential for effective analytics.
- The separation of compute from storage enhances scalability.
- Real-time processing with low latency improves user satisfaction.
Chapters
00:00 - Introduction to Real-Time Analytics
06:14 - The Evolution of Technology in Data Processing
10:09 - Challenges of Legacy Systems
14:23 - Innovative Approaches to Data Management
18:06 - Building a Foundation for AI Innovations
21:27 - User Experience in Data Applications
137 episoder
Del
