EP 08Released January 28, 2025

Business Analytics: From Data to Decisions in Real Time

Liam Zhao

Principal Data Scientist

Liam Zhao has spent a decade building analytics dashboards and predictive databases for financial services. He specializes in low-latency analytics.

Liam Zhao joins us to discuss the shift from weekly business reports to live analytical consoles.

Waiting until the end of the month to review sales numbers or supply chain logs leaves companies vulnerable to problems. Real-time stream processing tools feed data straight from sensors and web apps to the dashboards.

Liam shares how financial institutions use this telemetry to detect fraudulent transactions within milliseconds, and how developers can structure databases to handle massive query volumes.

Episode Key Takeaways

1Connecting streaming pipelines like Apache Kafka to live charts.
2Developing real-time fraud detection systems for transaction flows.
3Training non-technical managers to interpret predictive models.
4The performance cost of executing continuous streaming calculations.

Episode Transcript Highlights

00:05

Sarah Jenkins: Welcome everyone to another episode of The Primine Podcast. Today we are talking about engineering challenges.

00:25

Liam Zhao: Thanks Sarah. When looking at this problem, many teams jump straight into the application layer without realizing the structural bottlenecks underneath.

01:05

Sarah Jenkins: That's a great point. How does that translate into long-term cloud scalability and efficiency?

01:40

Liam Zhao: Well, it's about minimizing network latency, designing standard schemas, and choosing the right compute locations.

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Business Analytics: From Data to Decisions in Real Time

Featuring Liam Zhao

00:0044 min

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