Discover

Discover

Discover

Description

The Discover task is used to visually explore and understand your data before performing deeper analysis. It allows users to select specific data fields and quickly generate an HTML summary report.

Why to use

This helps identify patterns, missing values, or data quality issues early in the workflow, making it easier to decide next steps in your analysis or model-building process.

When to use

When you want to Quickly understand the structure and quality of your data.

When not to use

Prerequisites

Any type of data will work.

Related Algorithms

Data Compare

Alternative Algorithms

Input

Input dataset.

Output

HTML summary report.

Statistical Methods used

Limitations


    • Related Articles

    • Introduction to Rubiscape

      Today, the world stands at the threshold of the Fourth Industrial Revolution. Data science and data analytics are identified as the pre-eminent accelerating factors to boost industrial, technological, scientific, and eventually human capacity. There ...
    • Latent Dirichlet Allocation

      Latent Dirichlet Allocation Description Latent Dirichlet Allocation is one of the popular methods in topic modeling. It is an unsupervised learning algorithm. LDA aims to identify and extract the topics from a large collection of text datasets. Why ...
    • Latent Dirichlet Allocation

      Latent Dirichlet Allocation Description Latent Dirichlet Allocation is one of the popular methods in topic modeling. It is an unsupervised learning algorithm. LDA aims to identify and extract the topics from a large collection of text datasets. Why ...
    • Rubiscape Spring '25

      Published On: 09 May 2025 New Features Rubistudio / Rubiflow Data Compare: The Data Compare task is added to flag differences in the numerical column based on values in the common columns from the predecessor. Profile: The Profile task is available ...
    • Time-series Data Preparation

      Time-series Data Preparation organizes and formats transactional data into time-series data to predict trends and seasonality in the data. Transactional data is timestamped data recorded over a period at no specific frequency, while time-series data ...