Atlan > Case Studies > Democratizing Data: Postman's Journey to Streamline Data Access and Trust

Democratizing Data: Postman's Journey to Streamline Data Access and Trust

Technology Category

Analytics & Modeling - Data Mining

Applicable Industries

Cement

Use Cases

Immersive Analytics
Time Sensitive Networking

Services

System Integration

About The Customer

Postman is a leading API platform with hundreds of team members distributed across four continents. The platform is used by more than 17 million users from 500,000 companies. The company's data team scaled nearly fivefold in one year, leading to challenges in managing and understanding the data. Postman's goal is to democratize data, making it accessible and understandable to everyone in the company. This became especially important in 2020 when the company continued to scale while going fully remote during the COVID-19 pandemic.

The Challenge

When Postman's data team expanded, they faced a significant challenge in managing and understanding their data. The data was scattered across different locations, and often, the same data in different places contradicted each other. As the company grew, the data system, which was initially simple and manageable, became complex and difficult to navigate. The data was stored in tables, and the information about these tables was only known to the early members of the data team. This system was not scalable and could not keep up with the company's exponential growth. The company's goal was to democratize data, making it accessible and understandable to everyone in the company. However, the lack of consistency and context around the data made it difficult for everyone to understand and trust the data. The data team was constantly bombarded with questions about data location and usage, and the loss of any team member would mean the loss of crucial data knowledge.

The Solution

Postman's data team decided to take on the data system as a project, aiming to make the data easier to access and understand. They started by creating a Confluence document to store all data questions and answers that were previously stored in Slack. This document served as a single, searchable source of truth. However, as the company continued to grow, a single document was not scalable. The team then created a data dictionary in Google Sheets, where all table, schema, and column names were documented. However, this solution also faced challenges in terms of quality and scalability. Finally, the team implemented Atlan, a modern data workspace, which allowed them to catalog and document all their data. Atlan provided multiple levels of permissions for different types of users, enabling everyone to search for and access data without having to contact the data team. This solution ensured consistency across the board and helped rebuild trust in the data.

Operational Impact

Implementing Atlan as a data workspace has been a success for Postman. It has a clean interface and powerful functionalities, providing documentation, ownership information, usage, and data discovery. The workspace has enabled everyone to find the right data for their use case, and the data is consistent across the board for all accessing it. This has helped rebuild trust in the data. The workspace has also set up a system to track data, which can be used to understand data lineage, helping solve daily bugs and issues quicker. It has also opened up avenues for maintaining more consistent data descriptions across tools, improving data quality, and more. This has laid the foundation for democratizing data across the company, enabling the entire company to become more data-aware and data-driven.

Quantitative Benefit

Postman has over 17 million users from 500,000 companies.
The data team scaled nearly fivefold in one year.
Postman has about 170 active users per week on Looker, a significant number for a company of around 400 people.