Altertable

Insights

Insights are the primary way to create persistent visualizations and analyses in Altertable. They are saved analytics views that help you track key metrics, understand trends, and make data-driven decisions.

What are Insights?

Insights transform raw data into actionable visualizations by:

Query logic: query your lakehouse data using predefined logic
Visualization types: support charts, tables, and metrics
Refresh: refresh automatically or on-demand
Sharing: share with teams and embed in external tools

Prerequisites: Insights analyze data in your lakehouse. Start by connecting catalogs or creating a managed Altertable catalog.

Insight Types

Altertable offers semantic and SQL insight types for lakehouse data. For product-behavior analyses, see Product Analytics visualizations.

Insight Type	Best For	Key Feature	When to Use
Semantic	Business metrics	No-SQL query builder	KPI dashboards and reports
SQL	Custom analysis	Full query flexibility	Complex or ad-hoc queries

1. Semantic Insights

Semantic insights query semantic models using business-friendly metrics and dimensions—no SQL required. Define models, measures, and dimensions in the Semantic Layer, then pick them in the insight builder to chart KPIs and reports.

Best for:

Business metric reporting
KPI dashboards
Cross-functional analytics
Model-based queries

Example use cases:

"What's our monthly recurring revenue by region?"
"Show customer acquisition cost by marketing channel"
"Track product adoption metrics over time"

Semantic insight builder: choose a time grain, a business measure, and a chart type—preview updates from sample data

2. SQL Insights

Execute custom SQL queries using DuckDB dialect for complete flexibility in data analysis.

Best for:

Complex custom queries
Ad-hoc analysis
Advanced calculations (window functions, CTEs)

Capabilities:

Full DuckDB SQL dialect support
Cross-catalog federated queries
Advanced analytics functions (window functions, CTEs, recursive queries)
Complete query flexibility

Use cases:

Custom time-series calculations with specific business rules
Complex multi-source joins (events + CRM + revenue data)
Advanced grouping analysis with custom time windows
Performance analysis with moving averages and percentiles

Tasks on insights

Attach Tasks to insights to monitor them on a schedule:

Trend detection: get notified when metrics change significantly
Anomaly alerts: receive notifications when data deviates from patterns
Scheduled reports: generate periodic summaries

Tasks send Notifications when they find something noteworthy.

Creating Insights

Navigate to Insights
Click New insight
Choose Semantic or SQL
Configure the query and chart
Save and optionally attach a Task for monitoring

Learn More

Dashboards: combine insights into shared layouts
Tasks: scheduled monitoring on insights and other contexts
Notifications: notifications from tasks on insights
Memories: knowledge tasks build to improve monitoring over time
Semantic Layer: define metrics, dimensions, and model structure for semantic insights
Product Analytics visualizations: behavioral analysis over tracked product events
Ask AI: ask natural-language questions about your data
Lakehouse: query and connect data to your lakehouse