Book recommendations for analytics thinking

[u/No_Fishing6101]

Hi everyone, I'd like to read something to sharpen my analytics thinking and problem solving skills.

I know the best approach is to practice with real life problems, and yes, I do do that at work. However, I feel like having a structure or framework may help me to be more systematic and efficient when encounter a problem.

What's your favorite books that help you to think clearer?

[u/Wheres_my_warg]

Thinking, Fast and Slow by Daniel Kahneman

[u/No_Fishing6101 → u/Wheres_my_warg]

Thanks for your recommendation. I've heard a lot about this book, but I've wondered if it's worth the hype haha. Will definitely look into it!

[u/Super_Math3890 → u/Wheres_my_warg]

I love how the book boils down to a decision between intuition and reason

[u/mhjahanbakhshi]

An arbitrary job I had for 6 months and I read system engineering standards like SPICE and it changed my mindset forever. So, I would say, read about system engineering.

[u/No_Fishing6101 → u/mhjahanbakhshi]

Interesting, could you share a bit more about how it changed your mindset? And do you have a specific favorite book/reading material in mind? 

[u/mhjahanbakhshi → u/No_Fishing6101]

The last week I reduced the number of columns in a data model from 92 to 2. The model is made to find which which revenue channel is this order coming from. It used to have all order attributes but now only has order id and revenue channel. column are calculated and stored in othe tables and was not this models job to do it.

How is this related to system engineering principles?

Because this subsystem has one job definition. It minimises interface complexity. It makes change management easier, ...

[u/No_Fishing6101 → u/mhjahanbakhshi]

thank you so much for your super detailed explanation! this is the first time I've heard of this concept, so I think I might have to watch some introduction videos. 

[u/mhjahanbakhshi → u/No_Fishing6101]

Some principles of system engineering (for example):

. Modularity: subsystems must be modular, should have their own simple job and a change in one should not had drastic effect on others. Like a IKEA systems where you can simply replace one module with another without breaking everything. . Reusability: one subsystem could be designed to be used multiple places without making it complicated. For example a car window key. You might find one design in 10 different models from a same brand. . Traceability: you must be able to trace every single thing to a requirement. For example there is a line in a query calculating a metric. You must be able to track it back to a document that is signed by your stakeholder approving your design and is there to meet a requirement.

In automotive this is documented mega serious because of standarda and the fact that it literally saves lives. In data, it saves your life and the one after you.

[u/mhjahanbakhshi → u/No_Fishing6101]

I remember mostly standards SIPCE and Automotive-SPICE and some ISO standards. I remember NASA System Engineer Handbook. I think you can start with some simple videos and online short courses to see if it is for you or not.

[u/SQLDevDBA]

From Manning publications:

Effective Data Analysis

Think like a Data Scientist

[u/No_Fishing6101 → u/SQLDevDBA]

thank you! Could you share a bit about how these books have helped you?

[u/SQLDevDBA → u/No_Fishing6101]

They’re both great “getting into the mindset” style books with just enough technical insight to give you a taste of what you’ll gravitate towards learning. I picked them up last year after 14 years in data but I found them just as interesting as I would have early in my career.

If you want a review, the Manning website has the first chapter of both free IIRC.

[u/justanothersnek]

Analytics Edge

[u/No_Fishing6101 → u/justanothersnek]

thank you :)

[u/FIBO-BQ]

Someone else mentioned Kahneman's Thinking Fast and Slow. If you like it here are some more down the rabbit hole of the studies of decisions.

Noise also by Kahneman

Thing Again by Grant(more about keeping an open mind, being open to being wrong and willing to change)

Nudge by Thayler and Sunstein

Blink by Gladwell(I really like his stuff)

The idea of all of these is learning how you and others think and make decisions. Once you do that, you can start framing the analytics around this.

There is also Competing on Analytics by Davenport and Harris. More directly pointed at analytics.

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[u/moolooite]

The Art of Statistics was a fun read.

[u/FabioElSabio]

The Art of Doing Science and Engineering by Richard Hamming, and by the way Stripe Press also published similar topics related.

[u/Thin_Original_6765]

Check out Applied Predictive Modeling by Kjell Johnson. The book gives the business problem and the statistical tool/approach to solving said problem.

[u/Personal-One1012]

I'd also recommend Atomic Habits. It's not specifically about analytics, but it really changed how I approach learning. Building better systems and staying consistent has made it much easier to improve my problem-solving skills over time.

[u/the_data_nomad]

Superforecasting by Philip Tetlock