Here you will find a list of the capabilities in the Intelligent Exploration part of our platform, with links to more details:

• AI Analytics Routines:
  • Smart Mapping - helps you instantly understand the key drivers in your data.
  • Network Extractor - enables users to generate Network Graphs from tabular datasets.
  • Explainable AI (XAI) - provides succinct descriptions of relationships and insights.
  • Network Analysis Tools - various tools to support deeper analysis of Network Graphs.
  • Insights - automatically generated observations in plain English that are available for certain plot types.
  • Natural Language Query (NLQ) Assistant - enables you to input query text expressed in natural language and return relevant visualizations.
  • Clustering - groups points by numerical similarity.
  • Anomaly Detection - identifies points that are statistical outliers or have extreme values for combinations of features.
  • Principal Component Analysis (PCA) - reduces the complexity of a problem by condensing information from many different features into just a few representative features.
• Plot Types:
  • Scatter Plot - a common plot type that visualizes each row in your dataset as a single point on either a 2D or 3D plotLine Plot.
  • Histogram - used to group rows in your data into different bins.
  • Line Plot - allows you to track how certain metrics change with respect to another feature, with your data points connected by straight lines.
  • 2D Map - a way of visualizing geospatial data, or data with locations, on a smaller, 2D scale.
  • 3D Globe - a way of examining geospatial data, or data with locations, on a larger 3D scale.
  • Network Graph - a way of depicting entities and the relationships that exist between them.
  • Violin Plot - spreads out overlapping points so that you can better see areas of high concentrations of points.
  • Ellipsoid - adds confidence intervals displayed as 2D or 3D ellipsoids.
  • Convex Hull - adds shapes that outline all points of each color.
  • Surface Plot - creates a continuous surface from your data in either 2D or 3D to view how one feature is affected by two others.
• Data Sources:
  • Local Files:
    • CSV – A Comma Separated Values file.
    • Excel spreadsheet – Virtualitics will allow users to select the worksheet from the ‘Worksheets’ dropdown with multiple sheets.
    • Text file – Note: Must specify the delimiter used to separate values in the Dataset Preview window.
    • JSON file – A specific file type for loading in network data (see Network Data Formats).
    • VIP Project – A saved Explore project with a “.vip” extension.
    • OBJ file (Desktop only) – A standard 3D image format which includes 3D coordinates, texture maps, polygonal faces, and other object information.
  • Remote Data Sources:
    • Snowflake
    • Databricks
    • MySQL
    • SQLServer
    • PostgreSQL
    • Redshift
    • Hadoop (via Hive or Impala servers)
    • URL - any of the supported local file types.
    • ODBC - other ODBC-compliant data sources can be connected as long as the required driver is installed.
• Tools:
  • Interactive Legend - see what each Color, Shape or Group represents and interact with these to quickly modify the visualization.
  • Spreadsheet View - a tabular view of your data that allows you to view distributions and create new features from the existing features in the data.
  • Filters - modify how much of your data you are viewing by restricting to a specified range for numerical and date features or specific values for categorical features.
  • Workflows - streamline future analysis by saving the steps you have taken in analyzing data or creating visualizations within a Workflow file.
  • Annotations - leave notes, commentary, or detailed explanations to communicate insights and document your analytics process.
  • Calculator (Desktop only)- perform calculations on existing features in your dataset to create new features to support your analysis.
  • Feature Creation - many specific functions to extract new features based on the features in your original dataset.
  • Statistics - provides the following useful statistics for the selected numerical feature: min, max, median, mean, standard deviation, sum. Also provides counts of unique values for categorical features.
  • History - a running audit of the steps a user has taken within a Explore project file, recording all updates made to the plot.
  • Find and Replace - find and replace specific values in your dataset.
  • Search - find specific words or phrases in the dataset's features.
  • Normalization - transforms tightly clustered data points or reels in skewed points to create clear visualizations and aid in understanding.
  • Scatter Matrix - a quick way to view all three 2D projections of your three-dimensional plot.
  • Info Panels - access detailed information associated with the selected points or bins.
  • Image and Video Capture (Desktop only) - capture images, GIFs, and videos within the Explore application so that static or dynamic visualizations and procedures can be shared outside of the application.
  • Region Selection - zoom into a user-specified area on a 3D or 2D map.
  • Keyboard Shortcuts (Desktop only) - quickly move, rotate, or scroll through visualizations and data between different screens within the application.
  • View Options - a quick way to adjust the view of the plot.
  • Grid Options - adjust the view of your plot by toggling the plot gridlines and tick marks.
  • Contextual Menu - provides many useful options just a click away.
• Dimensions:
  • Position (X, Y, Z) - Three spatial dimensions that form the foundation for all plot types.
  • Color - Another important dimension that drives many visualizations and AI routines.
  • Size - Useful for qualitatively comparing numerical values.
  • Shape - Identifies which data points fall into different categories.
  • Group By - A quick way to select and deselect categories.
  • Playback - Animate your data by stepping through different points in time or categories.
  • Transparency - Emphasize or de-emphasize points based on numerical or categorical features.
  • Halo - Highlight outliers or other categories of interest.
  • Pulsation - Highlight outliers or other categories of interest.
  • Arrow - Useful for qualitatively comparing numerical values.
• VR (Desktop only) - immerse yourself in your data to analyze your 3D visualizations in a 3D environment.
• Shared Virtual Office (SVO) (Desktop only) - a collaborative space where multiple users can connect, share visualizations, analyze data, and discuss insights with colleagues.
• Python API (pyVIP) - an API to send commands to Explore from a Python environment (notebook, script, etc.).