Data Wrangling

Question 1

What is Data Wrangling

Answer 1

Sorting,
cleaning,
and structuring
raw data so that it becomes reliable and usable for analysis.

Question 2

Why is data wrangling important

Answer 2

Because mistakes in data due to it being unreliable can cost a company millions or even billions of dollars.

Question 3

What are the 6 steps of Data Wrangling

Answer 3

Discovery, Structuring, Cleaning, Enriching, Verifying, Publishing.

Question 4

What is the Discovery stage

Answer 4

Familiarizing yourself with data
to get an idea of its content
and understand how it can be organized effectively.

Question 5

What is the Structuring stage

Answer 5

Transforming data so it is usable, such as making files the same type to ensure compatibility.

Question 6

What is the Cleaning stage

Answer 6

Removing errors and useless data to make sure the dataset is accurate and free of mistakes.

Question 7

What is the Enriching stage

Answer 7

Improving weak or incomplete pieces of data to make the dataset stronger and more valuable.

Question 8

What is the Verifying stage

Answer 8

Ensuring that the data is correct and accurate, since incorrect data can lead to costly mistakes.

Question 9

What is the Publishing stage

Answer 9

Finalizing the wrangled data so it is ready to be used or shared effectively.