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    Data Model Generator (DMG)

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    Data Model Generator (DMG) is your intelligent assistant for modern data modeling—designed to empower data modelers by automating and simplifying the creation of Entity-Relationship (ER) models. Acting as a smart co-pilot, it interprets business requirements, domain language, and existing data assets to generate precise logical and physical models aligned with enterprise standards. Rather than replacing the modeler, it enhances their productivity by suggesting relationships, inferring cardinality, enforcing naming conventions, and accelerating documentation. Whether you're starting from a blank canvas or refining a complex model, Data Model Generator streamlines the entire process—reducing manual effort, improving accuracy, and freeing up data architects to focus on strategic design decisions

    Overview

    Data Model Generator (DMG) is an AI-powered assistant built to enhance the productivity of data modelers by automating and streamlining the creation, refinement, and management of data models. Acting as a smart co-pilot, it helps data teams transform textual requirements, business context, and existing assets into accurate and scalable Entity-Relationship (ER) models tailored to enterprise standards and specific technology environments.

    Whether starting from scratch or optimizing legacy models, Data Model Generator understands structured and unstructured inputs including STTMs, requirement documents, or metadata exports and converts them into logical and physical models optimized for your target databases.

    One of the platform’s core strengths lies in its ability to understand domain context and infer relationships, cardinalities, and attributes intelligently. It supports various modeling techniques, including relational, dimensional, and Data Vault approaches. Whether you're building transactional systems, data warehouses, or hybrid solutions, the platform tailors its outputs accordingly.

    Data Model Generator doesn’t just generate models it helps refine and optimize them. It analyzes existing data models and offers recommendations for improvements, such as normalization adjustments, standardization of naming conventions, and removal of redundancies. This provides high-quality design while preserving enterprise modeling leading practices.

    Key Features:

    AI-driven modeling assistant that interprets business requirements and domain knowledge

    Automatic generation of logical and physical data models based on context and target platform

    Supports multiple modeling techniques: relational, dimensional, and Data Vault Context-aware inference of relationships, keys, and data types

    Smart model refinement, offering suggestions to improve and standardize existing models

    Flexible normalization support, from 1NF to 5NF

    Integration-ready exports: ER diagrams, DDLs, and metadata for popular tools

    Industry-aware modeling, aligned with taxonomies and standards across domains

    Potential Benefits:

    Accelerates modeling timelines by automating repetitive and manual tasks

    Improves model quality with AI-guided recommendations and standardization

    Bridges the gap between business and technical teams with natural language understanding

    Provides governance alignment through reusable patterns and adherence to enterprise rules

    Enhances collaboration by enabling consistent documentation and versioning

    Reduces dependency on scarce modeling expertise, empowering broader teams

    Future-proofs data architectures with scalable, adaptable design patterns

    Data Model Generator is effective for organizations seeking to modernize their data architecture, accelerate digital transformation, and maintain a competitive edge. Whether you are designing new applications, migrating legacy systems, or optimizing existing databases, Data Model Generator provides intelligence and automation.

    This is a professional services engagement to configure and deploy these agent(s) using AWS Generative AI services

    Highlights

    • AI-Driven Data Model Creation: Supports relational, dimensional, and Data Vault modeling with flexible normalization (1NF to 5NF), versioning, and export-ready outputs for tools providing adaptability across diverse data architectures and governance frameworks.
    • AI-Powered Contextual Understanding: Understands business requirements, domain language, and industry taxonomies to generate accurate, business-aligned logical and physical data models starting from text, STTMs, or existing structures.
    • Smart Model Refinement: Acts as a co-pilot for data modelers by offering intelligent recommendations to improve existing models, enforce naming standards, and maintain consistency accelerating delivery while enhancing quality and team collaboration.

    Details

    Delivery method

    Deployed on AWS

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    Pricing

    Custom pricing options

    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Vendor support

    Please reach out to deloittedataassist@deloitte.com  for additional information and support.