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AIQ: What Data Product Management Means for You

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Synaptiq has spent the last decade studying data and artificial intelligence (AI) across a wide range of industries. We’ve consulted with clients, conferred with partners, collaborated with competitors, and conducted research to understand how and why organizations leverage these technologies.

 


Our ultimate takeaway?

AIQ: a novel approach to data and AI, centered on 11 key capabilities shown to facilitate successful workflow integration and return on investment (ROI).

This blog post will deep-dive into one of the 11 capabilities: Data Product Management. We’ll discuss what it is, how it’s done (when it’s done right), and why it matters. Or, you can read an overview of AIQ, including all 11 capabilities, in our blog post, “AIQ: What We Mean & What You Stand to Gain.“

 


What is Data Product Management?

Traditional product management is the function that brings products to market. It includes elements such as market analysis, requirements management, user experience, release management, and value capture across the product lifecycle. Data Product Management is an extension of traditional product management, wherein data is the primary value and technology and data literacy are crucial. 

Data Product Management is one of the foundational AIQ™ capabilities. It informs Data Sourcing, Data Engineering, Business Intelligence, and Modeling capabilities, making it particularly essential.

 


Data Product Management Done Right

Successful Data Product Managers know how to identify viable business opportunities for data-driven automation, “deep” analytics (i.e., beyond typical spreadsheet functions), and data asset creation.  Additionally, they have a scientific mindset that leads them to approach product development efforts by conducting experiments or “feasibility studies” before assuming that existing data will meet their vision. 

Overall, Data Product Managers understand data. They know how to leverage modern technologies, such as relational databases, machine learning modeling, APIs, and data visualizations to generate value.

 


Why Data Product Management Matters

Huge, unprecedented technological advances have allowed early-adopters to disrupt industries, leaving the rest of the world playing catch-up. An organization needs Data Product Management to (i) guide investment in data-driven applications and processes to keep up with growing rates of adoption across industries and (ii) drive maximum return on investment. A Data Product Manager ensures that their organization does not waste money on data assets that are neither viable nor profitable. Ultimately, their purpose is to capitalize on data-related opportunities as the “CEO” of data products in their organization.

You can learn how Data Product Management fits into AIQ™ by reading our blog. Or, take our AIQ assessment to determine where your organization stands for each of the 11 capabilities.

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