The Analytics-as-Code Platform for Modern Data Teams.
Holistics is a cloud-based Business Intelligence (BI) and data modeling platform engineered for data-driven companies that prioritize governance and scalability. At its core, Holistics utilizes a proprietary Analytics-as-Code approach via Holistics Modeling Language (HML), which allows data teams to define their business logic once and reuse it across the entire organization. This technical architecture separates the data modeling layer from the visualization layer, ensuring that metrics remain consistent regardless of which dashboard they appear on. For 2026, Holistics positions itself as a specialized alternative to Looker, offering a Git-integrated workflow that treats BI like software engineering. It connects directly to major cloud data warehouses (BigQuery, Snowflake, Redshift, ClickHouse) without moving data into its own storage, adhering to a high-performance, 'push-down' query philosophy. The platform is designed to empower non-technical users with a drag-and-drop interface for self-service exploration while providing data engineers with the programmatic control of a Semantic Layer. Its ability to manage complex data relationships and its native Git-versioning make it a premier choice for mid-market and enterprise teams seeking to eliminate 'metric drift' and implement robust data governance protocols.
Holistics is a cloud-based Business Intelligence (BI) and data modeling platform engineered for data-driven companies that prioritize governance and scalability.
Explore all tools that specialize in self-service exploration. This domain focus ensures Holistics delivers optimized results for this specific requirement.
A DSL (Domain Specific Language) that allows developers to define metadata, relationships, and business logic in code.
Direct integration with Git providers allowing for pull requests, code reviews, and CI/CD for analytics.
Uses a non-blocking query architecture to handle multiple heavy data warehouse requests simultaneously.
Secure dashboard embedding via signed URLs or iframe components with passed-through filters.
Automatically generates visual maps showing the flow of data from raw tables to final metrics.
Allows users to write results of heavy queries back to the warehouse as persistent tables.
Programmatic access to the defined metrics, allowing other applications to query defined business logic.
Connect your SQL data warehouse (e.g., BigQuery, Snowflake, PostgreSQL).
Install the Holistics CLI for local development (optional but recommended).
Define data models using HML (Holistics Modeling Language) to map database tables.
Establish table relationships (joins) within the modeling layer.
Define reusable metrics (e.g., Gross Margin, MRR) as 'Measures' in HML files.
Sync your project with a Git repository (GitHub/GitLab) for version control.
Create Datasets by grouping related data models for end-user exploration.
Build interactive dashboards using the drag-and-drop report builder.
Configure Row-Level Security (RLS) to control data access based on user attributes.
Deploy to production and schedule automated delivery to Slack or Email.
All Set
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Verified feedback from other users.
"Users praise the modeling layer and Git integration for bringing software engineering rigor to BI. Some find the learning curve for HML steep compared to purely visual tools."
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