TED: The human insights missing from big data | Tricia Wang

The video discusses the historical use of oracles for decision-making and compares it to modern big data systems. It highlights the challenges companies face with big data, using Nokia as a case study of failing to recognize smartphone demand. The concept of quantification bias is introduced, emphasizing the need to integrate thick data, which includes qualitative insights, with big data for more comprehensive decision-making. The video concludes with examples of successful integration, such as Netflix's transformation through understanding binge-watching behavior.

What role did oracles play in decision-making in ancient times?

How does the speaker compare modern data systems to ancient oracles?

What are some examples of questions people ask modern data systems?

What challenges do organizations face when using big data?

How did Nokia's reliance on big data impact their business decisions?

In what ways can the quantification bias affect decision-making in organizations?

What lessons can be learned from the oracle of ancient Greece regarding modern data usage?

What is 'thick data' and how does it complement big data?

Why is it important to integrate both big data and thick data in decision-making processes?

What insights did Netflix gain by integrating thick data into their business model?