The correct answer is: C. Nearly 80% of data analysis is spent on the cleaning and preparing data.
Data wrangling, also known as data munging, is the process of transforming and mapping data from one format to another. It is a necessary step in data analysis, as it ensures that the data is in a format that can be easily analyzed. However, data wrangling can be a time-consuming and tedious process.
Data dredging, also known as data fishing, is the process of searching for patterns in data without a specific hypothesis in mind. It is often used in exploratory data analysis, but it can lead to false positives.
Data cleaning is the process of identifying and correcting errors in data. It is an important step in data analysis, as it ensures that the data is accurate and reliable.
Data preparation is the process of organizing and formatting data for analysis. It includes tasks such as removing duplicate data, filling in missing values, and converting data into a standard format.
In a 2012 study, it was found that nearly 80% of data analysts spend their time on data cleaning and preparation. This is because data is often dirty and incomplete, and it requires significant effort to make it suitable for analysis.
Data wrangling, data dredging, and data cleaning are all important steps in data analysis. However, data preparation is the most time-consuming and important step. It is essential to ensure that the data is accurate, reliable, and in a format that can be easily analyzed.