Books

Noise - Part III - Noise in Predictive Judgments

Noise - Part III - Noise in Predictive Judgments

Translations: RU

How to measure the noise in our daily decisions?

Which is better - expert judgment or mechanical prediction using very simple models/rules? Surprisingly, the model of you beats you! Even a simple regression model based on your past decisions!

How to make rules/models even less noisy? How can rules/models become more biased sometimes?

Why don’t people always use models (if they are so good) and still rely on their bad judgment?

When do we not need models?

Clean Architecture - PART VI - Details

Clean Architecture - PART VI - Details

Translations: RU
The book club of our company has chosen a new wonderful book for reading: Robert Martin - Clean Architecture - a Craftsman’s Guide to Software Structure and Design 👍 The part VI undermines some foundations 😀: Do you know that Database is a “detail”? An unimportant minor low-level non-essential feature that can be neglected in architecture design! Do you know the same about the Web? It is just an unimportant IO device that should also be neglected in architecture design!
Clean Architecture - PART V - Architecture

Clean Architecture - PART V - Architecture

Translations: RU
The book club of our company has chosen a new wonderful book for reading: Robert Martin - Clean Architecture - a Craftsman’s Guide to Software Structure and Design 👍 Fifth part of the book contains A LOT of useful information: What is software architecture? What type of interdependencies can exist? How to draw borderlines between components? What type of borders exist? How to distribute policies by the levels? What are business rules, entities and use cases?
Noise - Part II - Your Mind is a Measuring Instrument

Noise - Part II - Your Mind is a Measuring Instrument

Translations: RU

Interesting to learn how your mind makes judgments. Two types of judgments: predictive and evaluative. How to measure errors from bias and noise. How to measure the cost of noise. And how to deal with catastrophic consequences.

Drilling down the noise to three components: system noise, level noise, and pattern noise. How to measure (and compensate) the noises. Occasional noise as a part of pattern noise. How to compensate occasional noise: wisdom-of-crowds effect, crowd-within-the-one effect, second answer effect, and dialectical bootstrapping tool.

How the group work influences the noise. Informational cascade and social pressure cascade. How to deal with them. The effect of group polarization.

Noise - Part I - Finding Noise

Noise - Part I - Finding Noise

Translations: RU

Do you realize how seriously your organization is affected by bad decisions? There are two types of errors in human judgments: Bias and Noise. Bias is a very widely recognized problem, and you definitely heard about it. Noise is not so widely recognized. Yet, it affects MANY decisions in ALL the industries.

There is a huge Noise in government decisions. There is a huge Noise in commercial companies.

Noise can be made visible and can be reduced. It is harder to measure the noise in unique singular decisions, but it is still there and it still can be reduced.

Designing Data-Intensive Applications - Chapter 12 - The Future of Data Systems

Designing Data-Intensive Applications - Chapter 12 - The Future of Data Systems

Translations: RU
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.
Designing Data-Intensive Applications - Chapter 11 - Stream Processing

Designing Data-Intensive Applications - Chapter 11 - Stream Processing

Translations: RU
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 11 discovers all aspects about Stream Processing. If your system needs to process some data on-the-fly then your DEV team should learn this info. Approaches for transmitting events: Direct messaging, Messaging Systems and Partitioned Logs.
Designing Data-Intensive Applications - Chapter 10 - Batch Processing

Designing Data-Intensive Applications - Chapter 10 - Batch Processing

Translations: RU
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 10 discovers all aspects about big data Batch Processing. If your system needs to process some data then your DEV team should learn this info. Unix tools for batch processing and brilliant concept of pipes.
Designing Data-Intensive Applications - Chapter 9 - Consistency and Consensus

Designing Data-Intensive Applications - Chapter 9 - Consistency and Consensus

Translations: RU
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 9 tells about Consistency and Consensus in distributed systems. It covers the following topics: What is consistency and eventual consistency Linearizability. Why it is needed. Difference from Serializability.
Designing Data-Intensive Applications - Chapter 8 - The Trouble with Distributed Systems

Designing Data-Intensive Applications - Chapter 8 - The Trouble with Distributed Systems

Translations: RU
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 8 discovers non-database related problems of distributed systems. DEV teams should consider them when designing distributed software. Faults and Partial Failures. The need to build a reliable system from unreliable components.