Vertesia Documentation

Overview

The Data Platform is Vertesia's solution for unified data management, combining AI-powered schema creation, SQL analytics, and interactive dashboards in one integrated experience.

What is the Data Platform?

The Data Platform enables you to:

  • Manage structured data using DuckDB-backed DataStores
  • Import data from CSV, JSON, Parquet, and Excel files
  • Query data using standard SQL with DuckDB extensions
  • Create dashboards with Vega-Lite visualizations
  • Analyze data with AI assistance through specialized agents

Key Concepts

DataStores

A DataStore is a DuckDB database that stores your structured data. Each DataStore:

  • Contains one or more tables with defined schemas
  • Supports SQL queries with DuckDB's powerful analytics extensions
  • Provides automatic versioning for schema changes and data imports
  • Can be linked to a Collection for file-based data sources

Tables

Tables within a DataStore have:

  • Columns with types: STRING, INTEGER, BIGINT, FLOAT, DOUBLE, DECIMAL, BOOLEAN, DATE, TIMESTAMP, JSON
  • Semantic types for enhanced understanding: email, phone, url, currency, percentage, person_name, address, country, date_iso, identifier
  • Foreign key relationships with referential integrity
  • Indexes for query optimization

Dashboards

Dashboards are Vega-Lite visualizations backed by SQL queries:

  • Single or multi-panel layouts with vconcat, hconcat, or grid arrangements
  • Interactive selections for cross-filtering between panels
  • Query parameters with {{param}} syntax for dynamic filtering
  • Automatic versioning with named snapshots for important states

Projects

A Project links a Collection (files) with a DataStore (database):

  • Files in the Collection serve as data sources
  • The DataStore holds the structured, queryable data
  • Linked via dp:<project-slug> tag
  • AI agents can analyze files and automatically create schemas

Architecture

Collection (files)     DataStore (DuckDB)
      │                      │
      └──── dp: tag ───┘
            │
      Project linking
  • Tag-based linking: Collections and DataStores are connected through tags
  • GCS storage: DataStore files are stored in Google Cloud Storage
  • Versioning: Automatic versions created on schema changes and imports
  • Snapshots: Named snapshots protected from automatic cleanup

Use Cases

Business Intelligence Dashboards

Create interactive dashboards that visualize key metrics from your data. Combine bar charts, line graphs, and tables to tell a data story.

Data Analysis with AI

Use AI agents to explore your data, run complex queries, and generate insights. The AI can understand your schema and write appropriate SQL queries.

ETL and Data Import

Import data from various sources (CSV, JSON, Parquet) with atomic operations. Transform and clean data during import with column mapping and type conversion.

Schema Design

Let AI analyze your data files and suggest optimal database schemas with appropriate types, relationships, and indexes.

Next Steps

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