Realtime Analytics Unleashed: Unlocking the Potential of Data at Scale | Barkha Herman
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📩 In this session, Barkha Herman dives into the world of real-time analytics, exploring how data is processed and analyzed at scale. She covers key tools like Apache Pino, Kafka, and Streamlit, demonstrating how real-time data processing helps organizations improve efficiency. Learn how distributed data architectures and columnar databases solve performance bottlenecks in massive systems like LinkedIn and Uber.
🔍 In This Video, You’ll Learn About:
✅ Real-time vs. batch analytics
✅ How streaming data and event-driven systems work
✅ The importance of low-latency analytics
✅ The architecture behind Apache Pino and Kafka
✅ How companies like LinkedIn and Uber use real-time analytics
✅ Best practices for building scalable data systems
Timestamps:
00:00 🚀 Build Stuff Conference – Get Your Tickets!
00:22 Introduction to Real-Time Analytics
02:30 Data at Scale: From Batch to Real-Time
05:12 The Shift from Monolithic Data to Distributed Data
08:05 The Role of Kafka in Event-Driven Systems
11:35 Why Apache Pino Was Created
14:00 Real-Time Analytics in Action: LinkedIn’s Profile Viewer
18:50 The Problem with Monolithic Data Systems
21:10 Architecture Overview: Real-Time and Offline Servers
24:00 Columnar Databases and Their Efficiency
28:15 The Benefits of Using Apache Pino for Real-Time Queries
31:00 Implementing Real-Time Dashboards
35:00 Demo: Real-Time Data with Kafka and Apache Pino
38:25 Use Cases: Uber, LinkedIn, and Stripe’s Adoption of Pino
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