How long does it take to design a new data platform architecture?

Manually, architecture design alone typically takes 6+ weeks. 3X Forward Engineer analyzes your API specs, CSV/Excel schemas, and DDLs to generate a first architecture blueprint in 3 to 5 days, covering landing, staging, and analytical layers.

Can KPIs shape how a data model gets designed?

Yes. 3X Forward Engineer's KPI-Driven Architecture Design turns your stated business objectives and KPIs directly into the analytical layer, so every fact table, dimension, and grain is built for the reports you actually need, not a generic template.

What is medallion architecture and how many layers does it need?

Medallion architecture organizes data into progressive layers, typically three: a raw landing layer, a cleansed staging layer, and a business-ready analytical layer aligned to KPIs. Some builds add a fourth staging sub-layer depending on source complexity. The right count depends on source volume and how many transformation steps the data needs before it's analytics-ready.

What's the difference between Data Vault and Kimball modeling?

Data Vault separates raw, auditable history (hubs, links, satellites) from business logic, favoring traceability and change tolerance. Kimball builds business-friendly star schemas optimized for direct reporting and query performance. The right choice depends on audit requirements, source volatility, and how directly the model needs to serve BI tools.

How are hidden relationships found in source data?

3X Forward Engineer maps cross-source flows, implicit joins, and hidden dependencies that aren't documented anywhere, using Graph-Based Source Understanding to catch relationships a manual review would likely miss when working from raw API and file specs alone.

Can a data platform be designed without an in-house architect?

Yes. 3X Forward Engineer embeds 25+ years of Distinguished-level architecture expertise into every design decision, so teams without a senior architect on staff still get architect-level output. This is the same engine that took a 48-source healthcare Patient 360 platform from raw feeds to an execution-ready design in under a week.

3X FORWARD ENGINEER

Design Modern
Data Platforms
Faster

3X Forward Engineer helps teams turn APIs, files, schemas, and source structures into modern data platform designs with production-ready models, DDL, ETL patterns, and implementation blueprints reducing weeks of architecture and modeling effort into draft outputs generated in days.

Platform Build — 6 API specs + 14 CSVs → Snowflake DW

Source Data Discovery & AnalysisComplete

6 APIs · 14 CSVs · 3 Excel schemas · 2 DDLs

Metadata & Relationship InferenceComplete

Graph-based dependency mapping & semantic analysis

Architecture Pattern DesignComplete

Generating Medallion / Kimball / Data Vault layers...

DDL & ETL Code GenerationComplete

Production-ready SQL, Python, Spark & orchestration

LANDING25raw tables

STAGING25cleansed

ANALYTICAL18KPI-aligned

DDL + ETL68scripts

Target Platforms

Code and schemas generated specifically for your target platform — leveraging platform-specific features and best practices.

Snowflake

SQL, Snowpark, stages, tasks

✓ TargetCloud DW

Databricks

Spark SQL, Delta Lake, Unity

✓ TargetLakehouse

BigQuery

Standard SQL, BigQuery ML

✓ TargetCloud DW

Microsoft Fabric

Synapse, OneLake, pipelines

✓ TargetFabric

How Does 3X Forward Engineer Work

A multi-stage intelligent pipeline that analyzes, designs, and generates your entire data platform automatically.

Convert Source Specs and KPIs Requirements into Architecture, Data Models, and Code

SOURCE DATA SPECS

3X FORWARD ENGINEER

DELIVERABLES

API Specifications & Endpoints

CSV/Excel Schemas

JSON/Flat Files

Source Database DDLs

Business Objectives & KPIs

Missing Metadata
Manual Architect Effort
Inconsistent Modeling Standards
Months of Design & Build

Multi-Source Input Analysis

Intelligent Metadata Inference

Graph-Based Source Understanding

Architecture Pattern Design

Complete Layer Design

Production-Ready Code Generation

Layered Architecture Design with Data Models

Production-Ready DDL & ETL Code

Medallion/Data Vault/Kimball Models

Distinguished Architect-Level Solution

ETL Pipeline Code (SQL / PySpark / Python)

Data Quality Validation Scripts & Lineage Documentation

Design Modern Data Platforms Faster