Data Science Lab
  • What is Data Science Lab?
  • Accessing the Data Science Lab Module
  • Data Science Lab Quick Start Flow
  • Project
    • Environments
    • Creating a Project
    • Project List
      • Keep Multiple Versions of a Project
      • Sharing a Project
      • Editing a Project
      • Activating a Project
      • Deactivating a Project
      • Deleting a Project
    • Tabs for a Data Science Lab Project
      • Tabs for TensorFlow and PyTorch Environment
        • Notebook
          • Ways to Access Notebook
            • Creating a Notebook
            • Uploading a Notebook
          • Notebook Page
            • Preview Notebook
            • Notebook Cells
              • Using a Code Cell
              • Using a Markdown Cell
            • Modifying a Notebook
            • Resource Utilization Graph
            • Notebook Taskbar
            • Notebook Operations
              • Datasets
                • Copy Path (for Sandbox files)
              • Secrets
              • Algorithms
              • Transforms
              • Models
                • Model Explainer
                • Registering & Unregistering a Model
                • Applying Filter
              • Predict
              • Artifacts
              • Variable Explorer
              • Find and Replace
          • Notebook List Page
            • Export
              • Export to Pipeline
              • Export to GIT
            • Notebook Version Control
            • Sharing a Notebook
            • Editing a Notebook
            • Deleting a Notebook
        • Dataset
          • Adding Data Sets
            • Data Sets
            • Data Sandbox
          • Dataset List Page
            • Preview
            • Data Profile
            • Create Experiment
            • Data Preparation
            • Delete
        • Utility
        • Model
          • Model Explainer
          • Import Model
          • Export to GIT
          • Register a Model
          • Unregister A Model
          • Register a Model as an API Service
            • Register a Model as an API
            • Register an API Client
            • Pass Model Values in Postman
          • AutoML Models
        • Auto ML
          • Creating Experiments
            • Accessing the Create Experiment Option
              • Configure
              • Select Experiment Type
          • AutoML List Page
            • View Report
              • Details
              • Models
                • View Explanation
                  • Model Summary
                  • Model Interpretation
                    • Classification Model Explainer
                    • Regression Model Explainer
                  • Dataset Explainer
            • Delete
      • Tabs for PySpark Environment
        • Notebook
          • Ways to Access Notebook
            • Creating a Notebook
            • Uploading a Notebook
          • Notebook Page
            • Preview Notebook
            • Notebook Cells
              • Using a Code Cell
              • Using a Markdown Cell
            • Modifying a Notebook
            • Resource Utilization Graph
            • Notebook Taskbar
            • Notebook Operations
              • Datasets
                • Copy Path (for Sandbox files)
              • Secrets
              • Variable Explorer
              • Find and Replace
          • Notebook List Page
            • Export
              • Export to Pipeline
              • Export to GIT
            • Notebook Version Control
            • Sharing a Notebook
            • Editing a Notebook
            • Deleting a Notebook
        • Dataset
          • Adding Data Sets
          • Dataset List Page
            • Preview
            • Data Profile
            • Data Preparation
            • Delete
        • Utility
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On this page
  1. Project
  2. Tabs for a Data Science Lab Project
  3. Tabs for PySpark Environment
  4. Dataset
  5. Dataset List Page

Data Profile

Data profiling refers to the process of examining and analyzing data to understand its structure, quality, and content.

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Last updated 2 years ago

Check out the given illustration to get full view of the Data Profile option.

Data profiling is a critical step in the Data Science model creation process. Data profiling involves analyzing and assessing the quality of data to identify any issues or anomalies that could affect the accuracy and effectiveness of the data science model. By performing data profiling, data scientists can gain insights into data quality, structure, completeness, and consistency, which helps them make better decisions about data preprocessing, data cleaning, and data transformation.

Steps to view the Data Profile:

  • Navigate to the Dataset list.

  • Select a Dataset from the list.

  • Click the Data Profile icon.

  • The Data Profile page opens displaying the Data Set information, Variable Types, Warnings, Variables, Correlation chart, missing values, sample.

Please Note:

  • Check out the illustration provided in the beginning to get the full view of the Data Profile page.

Refer the Data Science Lab Quick Start Flow page to get an overview of the Data Science Lab module in nutshell. to get redirected to the quick start flow page.

Click here
Data Profile