Introduction To Problem-Solving And Critical Thinking - Issue 144

The basics of analysis - steps of the analytical process, main techniques, and methodologies for informed decision-making.

Welcome to the Data Analysis Journal, a weekly newsletter about data science and analytics.

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You’d be surprised how many data scientists and analysts know very little about the methods and techniques of data analysis. Problem-solving doesn’t start with coding, but rather with critical and analytical thinking. This style of thinking is difficult to develop, especially if you are self-taught. It takes time and practice to train your mind. This is the main reason why many skilled analysts fail with technical challenges during interviews. Not because they don’t know how to write SQL, calculate LTV, or sort arrays in Python, but because they are distracted with details, pick the wrong algorithm, and (most commonly) miss signals provided in their task or input data. 

In this publication, I’ll cover:

• The basics of problem-solving and informed decision-making.

• How to develop critical thinking and strengthen your analytical intuition. 

• The lifecycle of analysis - its steps and process. 

• Common methods and types of analysis. 

Today’s publication is a little different. It’s tied to academia more than usual.

When I launched my journal, I had a strong objective to bridge the gap between academia and the industry. Today we use less than 20% of what we learned back at school, and we’re generally fine. And most career successes that many people have are not bolstered by knowledge, but rather by coincidence, luck, politics, or appearance. Fortunately, graduates don’t know this yet. And before they do, I want to show the new generation of analysts that there is another route to success via decent skills and an unshakably strong foundation of knowledge. 

So today, it’s all analysis 101. Please, take a seat.

Critical thinking and analysis techniques