3 Myths Discouraging Data Science Enthusiasts

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The term Data Science has become so popular in recent years. Numerous people are starting their careers in Data Science and aiming to become Data Analysts, Data Engineers, and Data scientists without even knowing “What is Data Science”.

What is data

But before understanding what Data Science actually is, let us first understand what is data? Whenever we hear the word data, we imagine it is a byproduct of some deep investigation or result of long-tiring research. Which is completely wrong! Well, it is every click you make, every search you do, every card you swipe, every song you listen to, every video you react to, every subscription you make. In short, each activity we do online is recorded and is used in some way or another. You are an enormous source of generating data alone. Contrary to our belief, it isn’t collecting data tedious, it is applying that data in meaningful terms.

Humans are data producers who provide tons of useful data to data-hungry companies. Even if you are watching funny cats’ videos at 2 am, you are providing some quality data to them.

One more aspect to realize is data is unprocessed and raw. To make it meaningful and useful, we deploy data science models.

What is Data Science?

Data science is the study of data. After analyzing the patterns, data scientists gather some useful insights which help them solve real-world problems. Data Science is not about making complicated models, awesome visualization, or writing complicated codes, it is about using data effectively, ensuring it is impactful for the customer. Data scientists may deploy top-notch models, but if the customer isn’t satisfied or the model presented doesn’t give accurate results, it is not a job well done.

Pre-Requisites for Data Science

In today’s era, both the producers and consumers demand full efficiency for the product. This has called the need for data scientists and now we see approximately all companies either have or are connected to data scientists. The rise in need also created many myths for this profession, which are discouraging potential students who are very enthusiastic about this field.

It is commonly said that in order to start with Data Science, a student must have great command in Mathematics, Statistics, Python, which is far from true. Although statistics is important in this field, a beginner won’t find himself in many problems if his basic concepts such as mean, median, mode, variance, standard deviation, Kurtosis, and skewness are at par. Even when it comes to python, a good understanding of data types, escape sequences, and functions will give you a good start. There is nothing as being “pro” at any of the disciplines. Along the road, you will learn, eventually calling yourself an expert.

Data Science use cases

Data science is used for many objectives. Each company uses data science to obtain more satisfaction from their services for the people. Few are examples of seemingly impossible scenarios which are just a piece of cake with help from Data Science.

Even if you have a poor grasp on these topics, no need to worry. Internet is filled with numerous courses and you can begin with any course and boost up your learning.

Read about Data Science Stretigies here