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Sample prompts:

Show me examples of application descriptions

Try CRM example. CRM app for the law industry that helps to connect different departments of a company, such as sales, customer service, and marketing, organizing their notes, activities, and metrics into one cohesive system. It should also be able to track leads, their statuses, categories, contacts, and their respective owners

Try ERP example. This application is a robust ERP solution tailored for the manufacturing industry. It's designed to simplify the complexities of production, inventory, and workforce management. Here's what I should be able to manage with ease: 1. Raw Materials: Maintain an organized inventory of all raw materials, track usage, and set reorder levels. 2. Work Orders: Create and manage work orders for production runs, specifying materials, labor, and machinery needed. 3. Machinery: Keep a detailed log of all my manufacturing equipment, including maintenance schedules and downtime. 4. Quality Control: Implement quality checks at various stages of production, and maintain records for compliance. 5. Inventory: Monitor finished goods, know what's available for sale, and what's reserved or returned. 6. Suppliers: Manage my relationships with material suppliers, including contract terms, delivery schedules, and payment records. 7. Human Resources: Keep tabs on employee data, from skilled labor to managerial staff, including their roles, shifts, and payroll. With this ERP solution, I'll have a 360-degree view of my manufacturing operations, all accessible from a single dashboard

Ask me questions to help me better describe my app!

Authorflatlogic.com

Generated by ChatGPT

Text to DB Schema is a Generative Pre-trained Transformer (GPT) developed by Flatlogic. The primary purpose of this tool is to take application descriptions and convert them into consumable database schemas or create-table SQL statements.

This GPT can be extremely beneficial when designing and implementing database structures for applications based on their functionality and requirements.

For instance, if your application description includes a CRM app for the law industry, it will create some DB schema reflecting the components like sales, customer service, marketing, leads tracking, etc.

Similarly, a description of an ERP solution tailored for the manufacturing industry will result in schemas for raw material inventory, work orders, machinery logs, quality control documentation, finished goods inventory, supplier contracts, and human resources data.

Such conversion can simplify the process of creating databases for these applications, making them more organized and manageable. The utility of this GPT is not limited to the aforementioned examples; it is fully capable of converting any variety of application descriptions into corresponding database schemas and create-table SQL statements.

However, it requires the use of ChatGPT Plus to function effectively. In summary, Text to DB Schema leverages AI to take a large part of the grunt work out of the database design process, making it an invaluable tool for application developers and database administrators.