Creating Data Dictionary Using ChatGPT

This article highlights how ChatGPT can create data dictionaries within minutes, aiding data professionals in documenting data items. By leveraging ChatGPT's capabilities, professionals gain deeper insights, enhancing data management. A practical example demonstrates the efficiency and effectiveness of using ChatGPT in generating data dictionaries.

What is a data dictionary?

Data professionals, such as data engineers, data scientists, analysts, database administrators, and developers, face various data challenges, ranging from business requirement definition to data volume and speed management. To effectively tackle these difficulties, they require a comprehensive understanding of the data. Data dictionaries play a vital role in providing deeper insights into the data. A data dictionary serves as documentation for the data, encompassing names, definitions, and attributes of the database's data items. Its main purpose is to comprehend and describe the significance of data items in relation to the application, along with including data element metadata. Data dictionaries are indispensable in data projects as they contribute to success by offering valuable insights into the data.

Benefits of creating a data dictionary:
 

• Conquer data discrepancies 
• Facilitate data exploration and analysis
• Maintain data standards throughout the project
• Establish uniform and consistent standards for the project
• Establish data standards to control the gathered data and explain it across the project
   

A typical data dictionary has below components:

 Image 1 : Sample Database Schema with Data Attribute Name, Data Type & Constraints

As demonstrated in the example above, each database has a basic set of data about the data dictionary, but this information is insufficient when working with a database that has numerous tables, each of which may have multiple columns. 

Creating a practical data dictionary with ChatGPT

Data and natural language processing can be used by ChatGPT to produce in-depth knowledge on any subject. As a result, ChatGPT may be used to build instructive data dictionaries for any dataset.

       Image 2: ChatGPT to create Data Dictionary

Let’s understand the step-by-step process to create a data dictionary using ChatGPT:
 

Finding and copying the data

 Let us ask ChatGPT for one of the public datasets to create a data dictionary:

List of Data Sources recommended by ChatGPT

Now, I will download the csv file named Institutions.csv from the FDIC Bank Data API.

Image 4: Downloaded CSV file for FDIC Bank Data

Let’s use this data to create a data dictionary using ChatGPT.

Prepare ChatGPT

Let’s now prompt the GPT to create a raw data dictionary for the dataset that we picked above:

Image 5: Output Data Dictionary

Request Data Dictionary with additional information

Additionally, we can request that ChatGPT add new columns and other pertinent data to the output of the data dictionary. For instance, in the sample below, I've asked ChatGPT to add a new column called Active Loan and to provide descriptions to the columns based on its knowledge of banking.

 

Output Data Dictionary from ChatGPT with additional columns and information

We can now see that the data dictionary is updated which can be shared within the organization.

Conclusion

In conclusion, leveraging ChatGPT's capabilities expedites the creation of data dictionaries, enhancing data management for professionals. Its efficiency and insights empower successful data projects, making ChatGPT a valuable tool in the data professional's toolkit.

Author Bio

Sagar Lad is a Cloud Data Solution Architect with a leading organization and has deep expertise in designing and building Enterprise-grade Intelligent Azure Data and Analytics Solutions. He is a published author, content writer, Microsoft Certified Trainer, and C# Corner MVP.

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