What is a data product?

There are several definitions of the term
“data products.” Essentially, data products are reusable packages that contain the underlying data, tools, documentation and context required to access, understand and utilize the data to achieve specific business goals. Data products include data pipelines, schemas, machine learning models, user interfaces, governance policies and access mechanisms.

The composition of data products can vary, and they can be refined and combined to create new data products. They can range from general purpose to highly customized, depending on the specific functionality required to meet business objectives.

Key components

Context: Information needed to understand and use the data, including its business use case
Data: The main information in the product
Access: Ways to get and work with the data

Examples

Sales dashboard: Provides near real-time insights into sales performance with visualizations and filters
Customer segmentation dataset: A curated dataset identifying customer groups for targeted marketing
Fraud detection model: An AI model that flags suspicious transactions based on historical data

Data-as-a-product vs. data products

Using product management principles to enhance the use and value of data is known as data-as-a-product. It involves ensuring that it’s built, managed and delivered, focusing on the end-user’s needs.

Data products are the output of treating data as a product. They are packaged entities that include data and other contents such as relevant metadata, pipelines and documentation, resulting in valuable curated data assets.

Although the data-as-product approach and data products are commonly associated with the data mesh methodology, not all organizations need data mesh to benefit from these concepts.

Read our blog to learn how you can get started with data products

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