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How people should learn by watching outcomes and why they do not learn?

There are many unknown circumstances - so we do not know the real cause of the outcome. Luck also plays a big part here, so we don’t know if it’s luck or skill.

Also we are distorted with our biases:

• self-serving bias
• and inverted self-serving bias

How to overcome our biases and learn better?

Earlier the book club of our company has studied excellent book:

Martin Kleppmann - Designing Data-Intensive Applications

This is the best book I have read about building complex scalable software systems. 💪

As usually I prepared an overview and mind-map.

Chapter 12 is a summary of the book and a visionary view of the future.

• Data Integration.
  • Overview of the ways we have to integrate data.
  • Causality and why we need Total Order and Idempotency.
  • Transactions and Linearizability
  • Limitations of Total Order.
  • Lambda architecture and unifying batch and stream processing as the most perspective approach.
• Unbundling Databases.
  • Overview of composing data storages together.
  • Designing apps around Dataflow.
  • Usage of derived states.
• Aiming for Correctness: what problems to consider and how to deal with them.
  • End-to-end fencing token.
  • How to process multi-partition requests.
  • Timeliness and Integrity issues. Apology workflow in business.
  • Meta approach: Trust, but Verify.
• Doing the Right Thing.
  • Predictive Analytics is discriminating people! We have responsibility and accountability here.
  • Privacy is conflicting with Tracking. Total surveillance should be legislated and self-regulated.

Download full mind map (PDF)