The stage of the data science process helps in converting raw data to a machine-readable format.

During data cleaning, raw data is converted into a format understood by the machine.

Data cleaning maybe explained as a variety of processes which is performed in other to tidy data values such as deletion of unwanted values, fixing missing errors, dealing with duplicate rows and so on. The data cleaning process takes a major percentage of the time used in Analysing a data. As this is the stage whereby the datasets to be used are prepared and set up to undertake the analysis process. Data Description involves highlighting the different types of data one will be using for the process. Data gathering involves sourcing for the data which one will require to carry out a certain analysis. They usually involves obtaining day from different sources. Exploratory data analysis involves preliminary evaluation of the data available. It includes making plots and obtain basic statistical information about the data at hand.

Therefore, converting raw data to machine readable format is performed during the data cleaning process.

Options provided :

Data gathering Data cleaning Data Description Exploratory data analysis

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The answer is "Data Cleaning".

Explanation:

In the given question some information is missing, that is the option of the question, which can be described as follows:

A) Data Gathering

B)  Data Description

C)  Data Cleaning

D) Exploratory Data  Analysis

Information cleaning is the method of processing information, that may not be accurate, complete, obsolete, replicated. It is used in to review the deleted and changing information, and certain options choice is incorrect, that can be explained as follows:

In option A, It is used in collecting data. In option B, It provides the details about the data. In option D, It is used in the statistical model for analyzing the data.