April 29, 2024
Updated June 6, 2024
4 minute read
Data Product Managers are responsible for the development and management of data products. They work with data scientists, engineers, and other stakeholders to define the requirements of a data product, and then oversee its development and implementation. Data Product Managers must have a strong understanding of data science, product management, and business analysis. They must also be able to communicate effectively with both technical and non-technical stakeholders.
Data Product Managers: What They Do
Data Product Managers are responsible for a wide range of tasks, including:
- Defining the requirements of a data product
- Overseeing the development of a data product
- Implementing a data product
- Managing the lifecycle of a data product
- Communicating with stakeholders about a data product
- Analyzing the performance of a data product
- Improving the performance of a data product
- Developing new data products
How to Become a Data Product Manager
There are a number of ways to become a Data Product Manager. One common path is to start as a data scientist or data engineer, and then move into a product management role. Another common path is to start in a business analysis role, and then move into a data product management role.
Skills and Knowledge Required for Data Product Managers
Data Product Managers must have a strong understanding of the following:
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Find a path to becoming a Data Product Manager. Learn more at:
OpenCourser.com/career/jasyc1/data
Reading list
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A comprehensive guide to designing data-intensive applications. Covers a wide range of topics, including data modeling, data storage, and data processing.
A comprehensive guide to data products. Covers the entire data product lifecycle, from inception to retirement. Provides a good balance of theory and practice.
A comprehensive guide to data science for business. Provides a good overview of the different data science techniques and how they can be used to solve business problems.
A practical guide to data product management. Provides a good overview of the roles and responsibilities of a data product manager. Includes useful frameworks and templates that can be used in practice.
A practical guide to data analytics. Provides a good overview of the different data analytics techniques and how they can be used to solve business problems.
A concise guide to data pipelines. Provides a good overview of the different types of data pipelines and how to manage them.
A practical guide to data-driven marketing. Provides a good overview of the different types of data that can be used for marketing and how to use it effectively.
A practical guide to machine learning for data products. Provides a good overview of the different machine learning techniques and how they can be used to build data products.
For more information about how these books relate to this course, visit:
OpenCourser.com/career/jasyc1/data
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