Data Arrow

Data Arrow is a business-driven data modeling platform offered as a SaaS product by Kea-Data Private Limited. It is currently in public preview and aims to unify the data modeling journey from business concepts to implementation. The platform bridges Kimball dimensional modeling, dbt-compatible transformation generation, and graph model semantics, enabling teams to design governed models that flow directly into pipelines and reporting layers. The platform supports designing facts, dimensions, grain, and relationships using proven Kimball principles. It can generate dbt models, tests, and documentation from these business models, making it easier for analytics engineers to implement trusted transformations. Data Arrow also includes reverse engineering capabilities to visualize and document existing SQL or dbt models, helping teams modernize their data landscape. Additionally, it provides graph modeling and a Cypher-compatible semantic layer, supporting AI-ready and knowledge-driven data architecture. Data Arrow is built for data architects, data engineers, analytics engineers, graph and semantic teams, data consultants, and platform leads. It is designed to standardize modeling practices, reduce the gap between business requirements and engineering work, and deliver reporting-ready data marts. A typical use case is starting with business KPIs, designing a dimensional model, generating dbt transformations, and running them on PostgreSQL for governed reporting. The product is currently in public preview, allowing early adopters to access features and provide feedback. As a cloud-based platform, it offers a governed and collaborative environment for model-driven data engineering. It is positioned as an end-to-end solution for teams wanting to connect business models to transformation, engineering, and knowledge-driven development.

Category: Data
Pricing: Paid

Problem solved

Data Arrow solves the disconnect between business requirements and data implementation by providing a governed platform where users design Kimball-based dimensional models, generate dbt-compatible transformation code, and build graph semantic layers from one source of truth. This reduces engineering rework, ensures consistency, and enables trusted reporting and analytics.

Use cases

Design a Kimball dimensional model with facts, dimensions, and grain
Generate dbt models, tests, and documentation from a dimensional model
Reverse engineer existing SQL or dbt models to visualize and document lineage
Build a graph model and Cypher-compatible semantic layer for knowledge-ready data
Deliver reporting-ready data marts on PostgreSQL from business KPI concepts
Standardize data modelling practices across a data team

Audience

Developers
Data Scientists
Business Users
Enterprise
Startups

Pros

Bridges business models to Kimball dimensional modeling and dbt generation
Includes reverse engineering of SQL/dbt for modernization
Provides graph model and semantic layer with Cypher compatibility
AI-driven co-pilots assist throughout the modeling journey
Governed and centralized platform for data teams

Cons

Currently in public preview; features may change
Paid pricing model with no public details
No offline or on-premise deployment option
Limited documentation and community resources during preview
No open-source repository or public code base

Official website: https://data-arrow.kea-data.com/

Canonical LambdaBase page: https://www.lambdabase.com/tools/data-arrow

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Data Arrow

Paid

★ 1 • Updated Aug 30, 2026, 09:16 AM

Data Arrow is a business-driven data modeling platform offered as a SaaS product by Kea-Data Private Limited.

Use Cases ▼

Design a Kimball dimensional model with facts, dimensions, and grain

Generate dbt models, tests, and documentation from a dimensional model

Reverse engineer existing SQL or dbt models to visualize and document lineage

Build a graph model and Cypher-compatible semantic layer for knowledge-ready data

Deliver reporting-ready data marts on PostgreSQL from business KPI concepts

Standardize data modelling practices across a data team

What Problem It Solves ▼

Key Features ▼

✓

Bridges business models to Kimball dimensional modeling and dbt generation

✓

Includes reverse engineering of SQL/dbt for modernization

✓

Provides graph model and semantic layer with Cypher compatibility

✓

AI-driven co-pilots assist throughout the modeling journey

✓

Governed and centralized platform for data teams

Overview

Full Description ▼

The platform supports designing facts, dimensions, grain, and relationships using proven Kimball principles. It can generate dbt models, tests, and documentation from these business models, making it easier for analytics engineers to implement trusted transformations. Data Arrow also includes reverse engineering capabilities to visualize and document existing SQL or dbt models, helping teams modernize their data landscape. Additionally, it provides graph modeling and a Cypher-compatible semantic layer, supporting AI-ready and knowledge-driven data architecture.

Data Arrow is built for data architects, data engineers, analytics engineers, graph and semantic teams, data consultants, and platform leads. It is designed to standardize modeling practices, reduce the gap between business requirements and engineering work, and deliver reporting-ready data marts. A typical use case is starting with business KPIs, designing a dimensional model, generating dbt transformations, and running them on PostgreSQL for governed reporting.

The product is currently in public preview, allowing early adopters to access features and provide feedback. As a cloud-based platform, it offers a governed and collaborative environment for model-driven data engineering. It is positioned as an end-to-end solution for teams wanting to connect business models to transformation, engineering, and knowledge-driven development.