5 Ways ChatGPT can support Data Vault in 2025

Large Language Models (LLMs) like ChatGPT have introduced unique opportunities for almost every industry. It is like having an all-knowing colleague sit at your desk with you, ready to respond to your queries instantly. However, there are important things to remember if you want to truly harness the power of ChatGPT when working with Data Vault.

What is ChatGPT?

Trained on a large section of the internet, ChatGPT excels in understanding and generating text in response to a diverse range of prompts. Its proficiency in natural language processing allows users to engage in conversations, pose queries, and receive coherent and contextually relevant responses. ChatGPT responses are based on a statistical best fit to the prompt you provide. In other words, its reply is not intelligent, it just seems that way, and in its attempt to please the questioner, it can make things up.

While boasting an impressive knowledge base, it’s important to note that at the time of writing this (April 2024), ChatGPT 3.5’s (the free version) information cutoff is April 2023, meaning that it cannot query up-to-date information. Despite this limitation, its applications span a multitude of industries, offering valuable support in tasks such as ideation, entity recognition, and pattern recognition, making it a versatile and useful tool for helping you implement Data Vault.

5 ways ChatGPT supports Data Vault

1. Learning and Upskilling

The initial stages of Data Vault generation often require creative thinking from data professionals. ChatGPT can be an invaluable tool during for people new to Data Vault who may need a little support. Its ability to provide instant feedback and generate ideas fosters a collaborative environment for refining and enhancing skills when working with Data Vault. However, it’s crucial to approach ChatGPT’s responses as suggestions needing collaboration with human input.

2. Entity and Relationship Recognition

Navigating the complexities of data structures, especially when identifying entities and relationships, is an important process in Data Vault design. ChatGPT can aid data professionals in efficiently understanding and defining these elements. Its linguistic support streamlines the early phases of modelling, producing a straw man input to the modelling process. It can also review the end results of the modelling phase and make suggestions for improvement. Do this with caution! Data privacy regulations mean that you could be sharing sensitive information with ChatGPT in prompts, although it may seem private.

3. Draft Generation and Documentation

ChatGPT can be applied more immediately in documentation generation. Given SQL create statements, DDLs or other contextual information, ChatGPT can be used to generate human-readable documentation for the data warehouse and the business rules and ETL/ELT processes that surround it. ChatGPT significantly contributes to Data Vault structure generation by automating the routine aspects of the data model draft creation and documentation. This not only eases the process but also allows data professionals to focus their efforts on refining the generated structure.

4. Semantic Understanding for Queries

Effective communication is a cornerstone of successful Data Vault maintenance. ChatGPT’s semantic understanding capabilities play a pivotal role by allowing data professionals to articulate complex queries in natural language. While it can generate SQL, you need to provide the schemas as input. This may be unsafe information to provide to ChatGPT.

Can ChatGPT Build a Data Vault?

No, not yet. While ChatGPT is a useful tool for understanding and generating text, the construction of a Data Vault demands the expertise of experienced data engineers. Building a robust Data Vault involves navigating technical intricacies and understanding specific business rules. ChatGPT complements the human, excelling as a supportive companion throughout the journey, offering insights, speeding up and streamlining processes.