Datasets
Onboarded data sources with KPIs, dimensions, and domain knowledge that power every downstream feature.
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.
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 / Hyper Connected
- You want to change processing cadence, impact score weights, or third-party alert channels
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.
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.
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.
Hyper Connected
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.