Data Preparation
Data preparation is the process of collecting, cleaning, and transforming raw data into a format that can be easily analyzed and used for various applications.
Last updated
Data preparation is the process of collecting, cleaning, and transforming raw data into a format that can be easily analyzed and used for various applications.
Last updated
Data Preparation involves gathering, refining, and converting raw data is a critical step in data analysis and machine learning, as the quality and accuracy of the data used directly impact the accuracy and reliability of the results. The data preparation is to ensure that the data is accurate, complete, consistent, and relevant to the analysis. By using this action, the data scientist can make more informed decisions, extract valuable insights, and unveil concealed trends and patterns within the raw data.
Navigate to the Dataset list page.
Select a Dataset from the list.
Click the Data Preparation icon.
The Data Preparation page opens displaying the dataset in the grid format.
Apply the required transforms on the data set. E.g., Auto Prep option is applied on the displayed Dataset (The user can also use any transformation using the Transforms tab).
Since Auto Prep is selected the below screen appears.
Select or reject the listed transforms by using the checkbox under the Transformation List that appears for the Auto Prep option.
Click the Proceed option.
Provide a name for the Data Preparation.
Click the Back icon to go back.
While clicking the Back icon, a notification message appears to inform the users that the data preparation has been saved.
The user gets redirected to the Dataset list page.
Select the Dataset for which the Preparation was saved.
Click the Data Preparation icon for the same Dataset.
While opening the Dataset it redirects to the Preparation List displaying the saved data preparation.
Refer the page to get an overview of the Data Science Lab module in nutshell.
