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Documentation Index

Fetch the complete documentation index at: https://docs.datagenie.ai/llms.txt

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

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What Datasets is

Datasets are onboarded data sources with KPIs, dimensions, and domain knowledge that power every downstream feature. A Dataset is the operational definition of what DataGenie monitors autonomously — its KPIs, dimensions, time anchor, granularity, and anomaly detection configuration. Everything else in the product (Top Stories, Wisdom, Explorer, Dashboards) reads from this definition.
The fastest way to create a Dataset is through GO — describe your business problem in natural language and GO generates the Blueprint for you.

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When to use Datasets

  • You need to fine-tune KPIs, dimensions, or SQL transforms after GO onboarding
  • You want to configure or tune anomaly detection for specific KPIs (see Multi Yhat)
  • You want to set up multi-source monitoring with Nirvana / HyperConnected
  • You want to change processing cadence, impact score weights, or third-party alert channels

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What you get

Essential details

Dataset name, connection parameters, time anchor, SQL transformation, and tenant association.

Regular processing

Processing range, schedule (Daily / Weekly / Monthly), and thresholds.

Build your insights

KPIs, dimensions, computed attributes, and anomaly detection configuration — the autonomous monitoring surface.

Customize insights

Impact score weights and Filter Presets for Top Stories.

Third-party alerts

Slack, Teams, Email, and JIRA channels for alert delivery.

Nirvana datasets

Combine independently-onboarded sources into a virtual multi-source dataset — no ETL.

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How it works

Set the Time Anchor

Define which column represents the date/time dimension. This is the reference for all period comparisons and anomaly detection.

Define Business KPIs

Add the metrics DataGenie should monitor. Specify aggregation (Sum, Average, Count) and any SQL transformations.

Configure Columns & Dimensions

Mark which columns are dimensions and set their cardinality.

Set the Processing Schedule

Choose how often DataGenie re-processes the dataset — Daily, Weekly, or Monthly.

Configure Anomaly Detection

Assign an AD Group to your KPIs. See the Anomaly Detection guide for Multi Yhat, seasonality handling, and Nirvana inheritance.

(Optional) Compose a Nirvana dataset

Combine multiple independently-onboarded sources into a virtual multi-source dataset. Nirvana datasets inherit default AD Groups from their components.

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What’s next

Anomaly Detection & Multi Yhat

Configure detection models, AD Groups, and Multi Yhat baselines.

GO

Generate a Dataset Blueprint from a natural-language brief.

HyperConnected

Nirvana datasets — multi-source monitoring with no ETL.

RBAC & Access

Control who can view and edit dataset configurations.

Filter Presets

Scope autonomous detection to your team’s focus areas.

Autonomous Insights

Understand what happens once a Dataset is live.