Data science methodologies part 1

Hi till now we are able to know that what is data science ? and some fundamentals of Data Science. Now let us move one step. Now we will c...

Hi till now we are able to know that what is data science ? and some fundamentals of Data Science.
Now let us move one step. Now we will cover Data science methodologies.

What is the methodology?

A system of methods used in a particular area of study or activity is called methodology.

The Data science methodology aims to answer the following 10 questions.

It means From problem to a solution we have to answer 10 questions

From problem to approach we need to answer the following 2 questions...

what is the problem that you are trying to answer?
How can you use data to answer the question?

To work with data we need to answer the following 4 questions:

3. What data do you need to answer the question?

4. Where is the data coming from ( Identify all Resources) and how will you get it?

5. Is the data that you collected representative of the Problem to be solved?

6. What additional work is required to manipulate and work with data?
To Deriving the answer we need to answer the following 4 questions:
7. In What way can the data be visualized to get to the answer that is required?
8. Does the model used really answer the initial question or does it need to be adjusted.?
9. Can you put the model into practice?
10. Can you get constructive feedback into answering the question?

So if you answered all questions then you will get the most accurate answers

CRISP-DM METHODOLOGY:

The CRISP-DM methodology is a process of aimed at increasing the use of data mining over a wide variety of business applications and industries. The intent is to take case-specific scenarios and general behaviour to make them domain neutral, CRISP-DM is a six-stage process...