Introduction

Data Science is blend of various tools, algorithms, and machine learning principles with goal to discover hidden patterns from the raw data.In Data Science below points lies:   
   1)  Data Analysis
   2)  Machine Learning and Algorithms
   3)  Data Product Engineering

Data Analyst describe in past history of the data and other hand data Scientist not only exploratory analysis to discover inside from it but also apply varies machine learning algorithms and also it is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.

Machine learning is an algorithm or model that learns patterns in data and then predicts similar patterns in new data. For example, if you want to classify children’s books, it would mean that instead of setting up precise rules for what constitutes a children’s book, developers can feed the computer hundreds of examples of children’s books. The computer finds the patterns in these books and uses that pattern to identify future books in that category.

Data engineering is the process of designing and building systems that let people collect and analyze raw data from multiple sources and formats. These systems empower people to find practical applications of the data, which businesses can use to thrive.