Analysis Paralysis and the Peril of Infinite Knowledge

Analysis Paralysis and the Peril of Infinite Knowledge

In my opinion, a programmer can do his job in the most productive way by believing that he is always a student. There are always multiple paths by which to solve a problem with code.

Permanent Students

In my opinion, a programmer can do his job in the most productive way by believing that he is always a student. There are always multiple paths by which to solve a problem with code, and it takes experience to learn which is the best. We must constantly be learning, for the technology and methods improve so rapidly that without learning, we quickly fall behind our peers. I've been lucky in that most of the developers I've worked with so far have taken this "permanent student" philosophy to heart.

Due to this mindset, a lot of programmers and developers that I meet have a deep-seated need to understand all possible solutions to their problem. They must be able to take each one apart and put it back together blindfolded before they can feel comfortable that they comprehend what the solution is supposed to do. For the most part, this is a good thing. It enables us to learn, to gather more information, and use that data to create new and better applications.

As a programmer living in the age of technology, I cannot imagine how (or even if) programmers held this mindset before we had the Internet. It has put the sum of human knowledge at our fingertips; any problem we have is only a quick search away. Hard copy books, the learning paths our coding forefathers used, are quickly becoming irrelevent, and the Internet is opening doors faster than we can look into the rooms. We, the permanent students, have the ability to study anything we wish. And because we are smart enough to recognize that we are almost always not the first person to have a particular problem, it's really easy to assume that the Internet must be able to provide an answer.

Analysis Paralysis

But the sum of human knowledge is effectively limitless. We programmers crave knowledge; it is embedded within us, the foundation for our skills and experience. So what happens when people who have such a basic need to understand everything meet a limitless amount of information? In my experience, many programmers will enter a state known as analysis paralysis, an inability to make a decision because it is not obvious which solution is better.

internet data analysis

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Exploratory Data Analysis is a significant part of Data Science

Data science is omnipresent to advanced statistical and machine learning methods. For whatever length of time that there is data to analyse, the need to investigate is obvious.

Tableau Data Analysis Tips and Tricks

Tableau Data Analysis Tips and Tricks. Master the one of the most powerful data analytics tool with some handy shortcut and tricks.

Analysis, Price Modeling and Prediction: AirBnB Data for Seattle.

Analysis, Price Modeling and Prediction: AirBnB Data for Seattle. A detailed overview of AirBnB’s Seattle data analysis using Data Engineering & Machine Learning techniques.

What Is Data Analysis?

DISCLAIMER: absolutely subjective point of view, for the official definition check out vocabularies or Wikipedia. And come on, you wouldn’t read an entire article just to get the definition.

Exploratory Data Analysis

Suppose you are looking to book a flight ticket for a trip of yours. Now, you will not go directly to a specific site and book the first ticket that you see.