what is data science

What is Data Science, A Simple Explanation

Today, many industries need to implement data science to grow their business and increase their customer satisfaction. It because they produce the massive amount of data over years and they want to take advantage from that. But, did you know what is data science and what does a data scientist do?

In this article we will cover all about data science: the definition, why do we need it, what does a data scientist do, and how to become a data scientist.

What is Data Science?

According simplilearn explanation, Data science is the domain of study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions.

Usually, it uses complex machine learning algorithms to build predictive models based on requirements.

So it can be said that data science is a science that combines programming skills, mathematics skills, and statistics skills.

When we talk about it, it cannot be separated from terms data and big data. You can read more about What is Data and Big Data here.

Why do We Need Data Science?

Some people may be asking why do we need data science, what make it so important for their business. These following reasons will be help us to understand why do we need it.

  • Data without science is nothing

    Data is like pieces of puzzle. You will not know the picture (information) before you finish to arrange all pieces of puzzle (various data) in the right place.

    That analogy means data without science are meaningless pieces of information.

    Let us give an example to more understand this concept:

    Let say we have accident data in a mining company, we also have employee fatigue data.

    From accident data we can get some information like how many accident happen in a certain period, the cause of accident, etc.

    From employee fatigue data we can get some information like who is employee get fatigue today, how many times an employee got fatigue in a certain period, etc.

    Now, if we use data science to get correlation between that two (accident and fatigue), it will be insightful for mining company to prevent the incident through analysing correlation and trend of accident and fatigue.

    Further, we can make predictive model from that two. It will be helpful to predict when the accident will happen caused by fatigue condition, so it can be used to prevent or alarm before accident really happened.

    This example only using two data, imagine how many data in a mining company or in our company? We want to take an advantage from our data, don’t we?
  • Help us to make best decision

    Imagine we can predict future conditions rely on data science, we can prevent the worst case or we can make best strategy to increase our business growth.
  • Help us to increase customer satisfaction

    Through data science, we can learn more about our customer habit when they visit or shopping in our website. From that, we can give some offering that suit with their desire without we asking our customer one by one. Let the machine learning.

What is Data Scientist?

Data scientist is a person who work in data science field. Data scientist will work to deal with the requirement of data science implementation in a particular industry field.

What does a Data Scientist Do?

A data scientist gathers the business problems and analyzes data to get meaningful insight that will give best solution for particular problem.

A data scientist will do a series steps to solve business problems:

  • Gathering requirement, asking a series question to understand the real pain point from a particular business process.
  • Determining variables and data sets.
  • Collecting and assessing data sources.
  • Data cleansing, validating the data to guarantee uniformity, completeness, and accuracy.
  • Transforming data become suitable format for analysis.
  • Analyzing and identifying patterns and trends of data using machine learning.
  • Interpreting the data to find opportunities and solutions.
  • Preparing the results and insights to share with the appropriate stakeholders and communicating the results.

Now the remaining question is only how to become a data scientist. Well, we talk more about it in article How to Become a Data Scientist.