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Data
Data
- Fundamentals of data
- Data connections
- Stored data credentials
- AI Catalog
  AI Catalog
- Import data
  Import data
  - Import to DataRobot directly
  - Large datasets
    Large datasets
    
    Fast EDA for large datasets
    
    Hadoop scalable ingest
- Transform data
  Transform data
  - Automatic transformations
  - Interaction-based transformations
  - Feature Discovery
    Feature Discovery
    
    Feature Discovery projects
    
    Time-aware feature engineering
    
    Derived features
    
    Predictions
  - Manual transformations
- Analyze data
  Analyze data
- Pipelines
  Pipelines
Modeling
Modeling
- Fundamentals of modeling
- DataRobot workflow overview
- Build models
  Build models
  - Build models
    Build models
    
    Basic model workflow
    
    Feature lists
    
    Unlock Holdout
    
    Comprehensive Autopilot
    
    Add/delete models
    
    Frozen runs
    
    Model Repository
  - Advanced options
    Advanced options
    
    Additional
    
    Bias and Fairness
    
    External Predictions
    
    Feature Constraints
    
    Image Augmentation
    
    Partitioning and model validation
    
    Smart Downsampling
    
    Time series
- Model insights
  Model insights
  - Evaluate
    Evaluate
    
    Accuracy Over Space
    
    Accuracy Over Time
    
    Advanced Tuning
    
    Anomaly visualizations
    
    Confusion Matrix (for multiclass models)
    
    Feature Fit
    
    Forecasting Accuracy
    
    Forecast vs Actual
    
    Lift Chart
    
    Residuals
    
    ROC Curve tools
    ROC Curve tools
    
    Use the ROC Curve tools
    
    Select data and display threshold
    
    Confusion matrix
    
    Prediction Distribution graph
    
    ROC curve
    
    Profit curve
    
    Cumulative Charts
    
    Custom charts
    
    Metrics
    
    Series Insights
    
    Stability
    
    Training Dashboard
  - Understand
    Understand
    
    Feature Impact
    
    Feature Effects
    
    Cluster Insights
    
    Prediction Explanations
    Prediction Explanations
    
    SHAP-based Prediction Explanations
    
    XEMP Prediction Explanations
    
    Word Cloud
  - Describe
    Describe
    
    Blueprints
    
    Coefficients (preprocessing)
    
    Monotonic constraints
    
    Data Quality Handling Report
    
    Eureqa Models
    
    Model log
    
    Model Info
    
    Rating Tables
    
    GA2M output (from Rating Tables)
  - Predict
    Predict
    
    Make predictions before deploying a model
    
    Downloads tab
  - Compliance
    Compliance
    
    Model Compliance
    
    Template Builder for compliance reports
  - Comments
  - Bias and Fairness
    Bias and Fairness
    
    Per-Class Bias
    
    Cross-Class Data Disparity
    
    Cross-Class Accuracy
  - Other
    Other
    
    Insights
    
    Learning Curves
    
    Speed vs Accuracy
    
    Model Comparison
    
    Bias vs Accuracy
- Specialized workflows
  Specialized workflows
  - Bias and Fairness resources
    Bias and Fairness resources
    
    Bias and Fairness overview
    
    Bias and Fairness reference
  - Composable ML
    Composable ML
    
    Composable ML overview
    
    Composable ML Quickstart
    
    Modify a blueprint
    
    Create custom tasks
    
    Custom environments
    
    DRUM CLI tool
    
    Composable ML reference
    Composable ML reference
    
    Blueprints in the AI Catalog
    
    Model metadata and validation schema
  - Location AI
    Location AI
    
    Data ingest
    
    Exploratory Spatial Data Analysis (ESDA)
    
    Modeling
    
    Accuracy Over Space
  - Unsupervised learning
    Unsupervised learning
    
    Anomaly detection
    
    Clustering
  - Visual AI
    Visual AI
    
    Visual AI overview
    
    Build models
    
    Train-time image augmentation
    Train-time image augmentation
    
    About augmented models
    
    Transformations and lists
    
    Use case examples
    
    Model insights
    
    Tune models
    
    Visual AI predictions
    
    Visual AI reference
  - Out-of-time validation modeling
  - Multilabel modeling
- Time-series modeling
  Time-series modeling
- Business operations
  Business operations
  - No-Code AI Apps
    No-Code AI Apps
    
    Current Applications
    
    Create Applications
    
    Build applications
    
    Consume applications
  - Partner integrations
    Partner integrations
    
    Tools for Alteryx
    
    Excel Add-in
    
    Tableau Extension URL
  - Use case tracking
- Modeling reference
  Modeling reference
  - Modeling details
    Modeling details
    
    Data partitioning and validation
    
    Modeling process
    
    Leaderboard reference
    
    Model recommendation process
    
    Optimization metrics
    
    SHAP reference
    
    Generate AI Report
    
    Export charts and data
    
    Worker Queue
    
    XEMP qualitative strength
  - Eureqa advanced tuning
    Eureqa advanced tuning
    
    Tune Eureqa models
    
    Configure building blocks
    
    Building blocks reference
    
    Custom target expressions
    
    Error metrics
    
    Error metric guidance
    
    Row weighting blocks
Predictions
Predictions
- Real-time scoring methods
  Real-time scoring methods
  - Prediction API snippets
  - Qlik predictions
- Batch prediction methods
  Batch prediction methods
  - Batch prediction UI
    Batch prediction UI
    
    Make a one-time batch prediction
    
    Schedule recurring batch prediction jobs
    
    Snowflake prediction job examples
  - Batch prediction scripts
- Portable prediction methods
  Portable prediction methods
  - Scoring Code
    Scoring Code
    
    Scoring Code overview
    
    Download Scoring Code from the Leaderboard
    
    Download Scoring Code from a deployment
    
    Scoring at the command line
    
    Scoring Code usage examples
    
    JAR structure
    
    Generate Java models in an existing project
    
    Backward-compatible Java API
    
    Scoring Code JAR integrations
    Scoring Code JAR integrations
    
    Import to SageMaker
    
    Import to Azure ML
    
    Android integration
    
    Apache Spark API for Scoring Code
    
    Generate Snowflake UDF Scoring Code
  - Portable prediction server
    Portable prediction server
    
    Portable Prediction Server
    
    Portable batch predictions
    
    Custom model Portable Prediction Server
  - DataRobot Prime
    DataRobot Prime
    
    DataRobot Prime examples
- Prediction reference
MLOps
MLOps
- MLOps overview
- Deployment
  Deployment
- Lifecycle management
  Lifecycle management
- Performance monitoring
  Performance monitoring
- Governance
  Governance
Platform
Platform
- Account management
  Account management
  - Manage projects
  - Help resources
  - Notification center
  - Manage your account settings
    Manage your account settings
    
    Manage your profile settings
    
    Developer tools
    
    View membership assignments
  - MLOps compatibility
- Authentication
  Authentication
- Administrator's guide
  Administrator's guide
  - Workflow overview
  - Manage user accounts
  - Manage groups
  - User Activity Monitor
  - Deployment approval policies
  - Manage feature settings
  - Notification service
    Notification service
    
    Notification channels and policies
    
    Webhook event payloads
    
    Mute deployment notifications
    
    Maintenance notifications
  - Reference
    Reference
    
    Role-based access control
    
    User Activity Monitor reference
- Data and sharing
  Data and sharing
- Companion tools
  Companion tools
Release center
Release center
- Public preview features
  Public preview features
  - Data public preview features
    Data public preview features
    
    Python module in pipelines
    Python module in pipelines
    
    Python Module API Reference
    
    Progress information for Pipelines
    
    AI Catalog fast registration
    
    AI Catalog impact analysis
    
    Creating and managing data connectors
    
    Governance workflow support for Feature Discovery deployments
    
    Create feature lists in the Relationship Editor
    
    External OAuth for Snowflake
  - AutoML public preview features
    AutoML public preview features
    
    Quantile regression analysis
    
    Decision Intelligence Flows
  - Time series public preview features
    Time series public preview features
    
    Forecast point policies in job definitions
    
    Time series What-if applications
    
    Clustering for segmented modeling
    
    Deployment for segmented modeling
    
    Scoring Code for time series projects
  - MLOps public preview features
    MLOps public preview features
    
    Using the Tableau Analytics Extension with deployments
    
    Reset deployment analytics
    
    Multipart upload for the batch prediction API
  - Administrator public preview features
    Administrator public preview features
    
    Permanently delete users
    
    Custom RBAC roles
- Archived release notes
  Archived release notes
  - AutoML release notes
    AutoML release notes
    
    Version 8.0.x
    Version 8.0.x
    
    Version 8.0.3
    
    Version 8.0.2
    
    Version 8.0.1
    
    Version 8.0.0
    
    Version 7.3.x
    Version 7.3.x
    
    Version 7.3.6
    
    Version 7.3.5
    
    Version 7.3.4
    
    Version 7.3.3
    
    Version 7.3.2
    
    Version 7.3.1
    
    Version 7.3.0
    
    Version 7.2.x
    Version 7.2.x
    
    Version 7.2.8
    
    Version 7.2.7
    
    Version 7.2.6
    
    Version 7.2.5
    
    Version 7.2.3
    
    Version 7.2.2
    
    Version 7.2.1
    
    Version 7.2.0
    
    Version 7.1.x
    Version 7.1.x
    
    Version 7.1.4
    
    Version 7.1.3
    
    Version 7.1.2
    
    Version 7.1.1
    
    Version 7.1.0
    
    Version 7.0.x
    Version 7.0.x
    
    Version 7.0.3
    
    Version 7.0.2
    
    Version 7.0.1
    
    Version 7.0.0
  - AutoTS release notes
    AutoTS release notes
    
    Version 8.0.x
    Version 8.0.x
    
    Version 8.0.0
    
    Version 7.3.x
    Version 7.3.x
    
    Version 7.3.0
    
    Version 7.2.x
    Version 7.2.x
    
    Version 7.2.0
    
    Version 7.1.x
    Version 7.1.x
    
    Version 7.1.0
    
    Version 7.0.x
    Version 7.0.x
    
    Version 7.0.2
    
    Version 7.0.0
  - MLOps release notes
    MLOps release notes
    
    Version 8.0.0
    
    Version 7.3.0
    
    Version 7.2.0
    
    Version 7.1.0
    
    Version 7.0.0
  - Data Prep release notes
    Data Prep release notes
    
    Version 2021.2
    Version 2021.2
    
    Version 2021.2
    
    Version 2021.2 Addendum
    
    Data Prep platform support 2021.2
    
    Version 2021.1
    Version 2021.1
    
    Version 2021.1
    
    Version 2021.1 Addendum
    
    Data Prep platform support 2021.1
- Deprecations and migrations
  Deprecations and migrations
  - Python 2 deprecation / migration to Python 3
  - Batch Scoring Script (deprecated)
  - Transfer models
  - Deploy to Hadoop tab
    Deploy to Hadoop tab
    
    Using Hadoop Scoring from the command line
- Deployment history

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Platform > Companion tools > Paxata Data Prep > Connect to data sources for Data Prep > Google Sheets Connector

Google Sheets Connector for Data Prep¶

The Google Sheets Connector has been deprecated. Please use the Google Drive Connector, which has support for importing and exporting Google Sheets.

Updated April 12, 2022

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