Product Owner to Data Product Owner

Data product management is complex for several reasons.

First, data is often messy, incomplete, and challenging to interpret.

Second, there are typically multiple stakeholders involved in data product management, including customers, developers, data scientists, and business executives, each with different priorities and requirements.

Third, data products can have a wide range of use cases and applications, from marketing and sales to operations and finance, making it challenging to prioritize features and functionality.

To add to the complexity, data products require a deep understanding of the underlying data, including how it is collected, processed, and analyzed. This requires technical expertise and domain knowledge, which can be difficult to find in a single individual.

Understanding the value of a data product is critical to its success. A data product can be defined as any software tool that helps users make sense of data, such as a dashboard, analytics platform, or machine learning model. Without a clear understanding of the value a data product provides to its users, it can be challenging to prioritize features and ensure that the product meets the needs of its target audience.