Forecasting

Documentation Index

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Use this file to discover all available pages before exploring further.

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Setup

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Capabilities

• Time series forecasting — Predict future values based on historical trends and patterns in your data. Supports multiple time frequencies including hourly, daily, weekly, and monthly data.
• Anomaly detection — Flag unusual data points in historical time series by fitting prediction intervals and identifying values that fall outside the expected range.
• Confidence intervals — Return prediction ranges alongside point estimates so you can plan for best-case and worst-case scenarios.
• Exogenous variables — Incorporate external factors (such as promotions, holidays, or weather) into forecasts for more accurate predictions.

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Key Benefits

• No data science required — Get forecasts from historical data without building or maintaining statistical models.
• Built into any workflow — Include forecasting as a step in any assignment, combining it with data retrieval, analysis, and reporting.
• Range-based planning — Confidence intervals give you a realistic spread of outcomes, not just a single number.
• Broad applicability — Apply forecasting to demand planning, financial projections, inventory management, workforce scheduling, or any time-ordered dataset.

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Works Well With

• Snowflake, Google BigQuery, or Databricks — Query historical data from your data warehouse and feed it into the Forecasting connection to produce forward-looking projections.
• Google Sheets or Microsoft Excel — Pull forecast results into spreadsheets for planning, reporting, or sharing with stakeholders.
• Slack or Microsoft Teams — Post forecast summaries or alerts when projected values cross key thresholds.