Application Data Overview — Application Data

What Is the Application Data Pattern?

Traditional application development for data entry and retrieval requires writing backend controllers, service classes, data access layers, frontend components, and API contracts. The Application Data pattern in BizFirstGO replaces this entire stack with four components that you configure rather than code:

SQL Table

A Data Ocean SQL Server table with the standard schema convention — your business columns plus the required metadata and optional AI enhancement columns.

Atlas Form

An AI-generated Atlas Form that maps to the table columns. Fields, validation, and labels are generated from the schema — customizable in the form designer.

CRUD Workflows

Four Flow Studio workflows — Create, Read, Update, Delete — each using SQL nodes to write to and read from the table. No application code.

Data API

Each workflow with a REST trigger is automatically a REST API endpoint. External applications can call your data through standard HTTP — no custom API server needed.

When to Use the Application Data Pattern

Use Application Data Pattern	Consider Alternatives
Building line-of-business data entry applications (CRM, ticketing, inventory)	Real-time streaming data — use EdgeStream instead
Replacing spreadsheets with structured, queryable databases	Unstructured document storage — use Blob Storage
Creating data backends for Atlas Forms without writing API code	Existing legacy database with complex stored procedures
Multi-tenant SaaS applications where each tenant has isolated data	Graph relationships requiring a graph database
AI-enrichable data that will feed into Octopus workflows	Hot path transactional data needing sub-millisecond latency

Architecture Overview

User (Browser)
    └── Atlas Form (Submit)
            └── Form Action → REST Trigger
                    └── Flow Studio Workflow (Create/Update)
                            └── SqlUpdateNode
                                    └── Data Ocean SQL Server
                                            └── YourTable

External System (API Call)
    └── HTTP POST /api/workflows/{workflowId}/trigger
            └── Flow Studio Workflow (Read)
                    └── SqlQueryNode → JSON response
                            └── Data Ocean SQL Server

How This Guide Is Organized

Schema Design

Start with your business requirement. Translate it into a Data Ocean-compliant SQL table schema with the correct metadata columns.

AI Form Generation

Feed the SQL schema to the Atlas Form AI generator. Get a complete form definition with fields, validation, and SQL command bindings.

CRUD Workflows

Build the four CRUD workflows in Flow Studio. Each workflow handles one operation and uses SQL nodes to interact with the table.

Data API and Visualization

Expose read workflows as API endpoints. Connect query results to Atlas Form chart controls for real-time dashboards.

Access Control

Apply role-based access on workflow triggers, form fields, and row-level data visibility. Tenant isolation is enforced automatically.

End-to-End in Hours, Not Weeks

A complete Application Data application — schema, form, CRUD workflows, REST API, and basic dashboard — can typically be built in 4-8 hours using the no-code pattern described in this guide. See the End-to-End Example page for a complete walkthrough building a lead management application.

Next: Designing the Data Schema →