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 for a Repo Sync Project.
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. For example, Click the Auto Prep option to apply the default transforms that are part of Auto Prep.
The Transformations List gets displayed with the default transforms provided under the Auto Prep option.
Click the Proceed option.
Provide a name for the Data Preparation
Click the Back icon to go back.
A notification message appears to inform the users that the data preparation has been saved.
Once the user has saved a data preparation inside any Dataset, they will be redirected to the Dataset list page.
Select the same Dataset from the list where a Data Preparation is saved.
Click the Data Preparation icon for the same Dataset.
The Preparation List window opens listing all the saved data preparations for the concerned Dataset.
Refer the page to get an overview of the Data Science Lab module in nutshell.
