TIM Documentation Version 3.2
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    • Home
      • Overview
        • Introduction
        • Time Series Forecasting
        • Time Series Anomaly Detection
        • (RT)InstantML
        • Designed for time series
        • Realtime forecasting
        • Transparent models
        • Business benefits
        • Operational IT benefits
        • Overview
          • Input data properties
          • Uploading data
          • Updating data
          • Imputation
          • Timescale and aggregation
          • Filters
          • Date and time formatting
          • Cron notation
          • Relative time notation
          • Time zones
        • Overview
          • Overview
          • Structure
          • Model building
          • Model rebuilding
          • Lifecycle
          • Backtesting
          • Probabilistic forecasting and prediction intervals
          • Classification
          • Panel data
          • Overview
          • Features
          • Daily cycle
          • Overview
          • TIM forecasting output
          • Model Zoo
          • Root cause analysis
          • Error measures
          • Error and warning messages
          • RTInstantML production pipeline
          • Overview
        • Overview
          • Overview
          • Lifecycle
          • Engine schema
          • What problems TIM AD can solve
          • Overview
          • Sensitivity
          • Detection perspectives
          • Overview
          • Anomaly indicator
          • Root cause analysis
          • Error measures
          • Best practices
          • Design of experiment
          • Overview
          • Heat consumption
          • Wind turbine
          • Manufacturing production line
            • Overview
            • Heat consumption
        • Glossary
        • Overview
        • Version 5
        • Version 4
        • Version 3.2
        • Overview
        • On - premise deployment
        • Size your infrastructure for a TIM 5.0 implementation
      • Glossary
      • FAQ
      • Overview
      • Navigating TIM Studio
      • User Groups
      • Workspaces
      • Use Cases
      • Datasets
        • Overview
        • A Forecasting Experiment
        • An Anomaly Detection Experiment
        • The ModelZoo
      • User Profile
      • License
      • Settings
      • Use Case Templates
          • Introduction
          • Usage paths
          • Workspaces
          • Datasets
          • Model Building Definitions
          • Forecasting Screen
          • Detection Screen
          • Experiments
          • Overview
            • Quick start
            • What is new
            • Who can use TIM Studio
            • Navigation
            • Workflow
            • Datasets overview
            • Creating new Dataset
            • Dataset requirements
            • Exploring Dataset
            • Sampling period
            • Downloading data
            • Updating existing Dataset
            • Removing Dataset
            • What is your Use Case?
            • Creating new Use Case
            • Removing Use Case
            • What is an Experiment
            • Creating new Experiment
            • Back-testing and Iterations
            • Evaluating results
            • Removing Experiment
            • From experimenting to production
            • Creating new forecast
            • Managing forecasts
          • MLDevOps
            • Logging into TIM Studio
            • Resetting your password
            • Multi-user setup
            • About page
            • Roadmap
      • Overview
        • Overview
        • Installation
        • Authentication
          • Overview
          • TIM Forecasting tool
          • TIM Anomaly Detection Build model tool
          • TIM Anomaly Detection Detect tool
        • Introduction
        • Data update pipeline
        • Model building pipeline
        • Forecasting pipeline
        • RTInstantML pipeline
        • Triggering pipelines
        • Importing pipelines
        • Introduction
        • Adding TIM to Excel
        • Data Formatting
        • Using TIM in Excel
        • Hands-on Walkthrough Scenario
        • Overview
        • Using TIM in Power BI
        • Power BI Forecasting Template
        • Power BI Anomaly Detection Template
        • Overview
        • Installation
          • Authentication
          • Dataset Management
          • Forecasting
          • Anomaly Detection
          • Workflow Management
          • Status Polling
        • Transitioning from v1 to v5
            • Overview
            • Installation
            • Using TIM Python Client
        • Overview
        • TIM InstantML and Qlik
        • Example TIM in Qlik
        • Installation
        • The Functions of the TIM SSE
        • Getting Started with TIM in Qlik
        • Architecture of TIM in Qlik
        • Overview
        • Installation
      • Overview
      • TIM API
      • TIM Studio
      • TIM Edge
      • Alteryx Forecasting Tool
      • Alteryx Anomaly Detection Tools
      • Microsoft Excel Add in
      • Python Client
      • Qlik SSE
      • LTS

    Version 3.2

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