Data Science Tutorial
Introduction to data science
Data science helps the user by providing an ability to analyze huge data sets and by doing necessary operations, data science will save precious time and makes some big profit out of it.
Data science is very much popular in today’s world scenario as there is a huge amount of data generated each day in different fields like mart, hospitals, colleges, etc.
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Users need to perform some operations by analyzing the dataset and then find something useful from that data.
For example- Suppose there is a dataset of a mart, which contains data for 4 users.
|Users||Last visited||Last bought products||Average amount spent each time||Number of times visited in last month||Most bought products|
|Abhishek||13th Jan||Milk, eggs, bread, juice||200||10||Eggs, juice|
|Aditya||20 Jan||Cabbage, wheat, rice, soft drinks||500||5||Soft drinks, rice|
|Rahul||23rd Jan||Rice, pulses, wheat, ice cream, snacks, eggs||1000||4||Eggs, wheat|
|Sneha||15th Jan||Chocolates, Corn flakes, pen, tea bags||300||3||Chocolates, tea bags|
From above data, mart will predict products needed for each user and it will also predict when this user will be going to visit their mart.
For Sneha, mart knows that she will visit the shop for minimum 3 times in a month.
So, next date will be in the last week of January and recommended product will be chocolates and tea bags. Along with that mart will suggest some products so that she will be spending amount approx 300.
Solution to the problem should be logically solved by using mathematical skills and specific tools like R studio. Data science is a medium to analyze real-time data that enhance clarity and give the right solution to an enterprise.
This picture will tell the overview of data science course
Data Science Process
Step 1: Organize Data
It includes the physical storage and formatting of data and integrated finest practices in data management.
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Step2: Package Data
In this the prototypes are created, the visualization is built and also statistics is performed. It includes logically joining and manipulating the raw data into a new representation and package.
Step 3: Deliver Data
In this process data is delivered to those who need that data.
Data Science vs. Data Analysis
It’s very important to know that data science and Data analysis are little similar but, there so many differences between them. Let’s check out the differences
|Data Science||Data Analysis|
|Providing strategic actionable insights into the world||Providing operational observations into issues|
|Mathematical, technical and strategic knowledge are mandatory||Data analysis and visualization skills required|
|Deal with big data||Not necessarily deal with big data|
In brief, with the help of data science, we will be able to analyze datasets, understand it and by performing necessary operations, we will get the resultant which will be beneficial for users.