INTRODUCTION TO DATA SCIENCE.

Data science is a mainstream word that has thrown around the world a lot but its actual definition is vague. Basically data science is transforming data into information and then to knowledge in layman's language. Data itself in its raw form is not useful and that's why data scientists are needed to remove the vagueness of data that's in numerical form. Data is transformed to information through analysis of data to get insights, identifying trends, patterns and correlations as well as contextualizing, applying and understanding the data.
Data scientists have the role in companies to get data, process the data and convert it from its raw format to a cleaner format. They are also tasked with creating visualizations, drawing conclusions for analysis and suggest applications for implementations.
Data science basically involves 3 essential components;

1. Statistics
   Understand different data types that you can encounter because data can come in different ways depending on the field you are in. Also understanding key statistical terms such as means to help give an overview of how data is fluctuating. Also be able to split up, group and segment data points.

2. Data Visualization
   Data visualization is a key skill because it helps to show and compare different numbers of variables through graphs that allow for comparison of multiple things at the same time.

3. Programming
   Programming is really essential when it comes to data science as it makes it easy to automate, customize, explore, prototype and test the data. Programming helps you by removing roadblocks of depending on other people. Essential packages required in python are pandas for data analysis and other libraries.

Basically data science is about using data to create as much impact for company that can be in the form of insights, in the form of data products or in the form of product recommendations for a company. This is done by tools like making complicated models or data visualizations or writing code and this helps to solve real company problems using data.