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Strategic Data Methods: A Safari Tour for Data People

As data science and engineering work matures and evolves, our efforts become even more relevant to product-facing applications. Data scientists and engineers begin to work in a more cross-disciplinary environment. To facilitate this transition, we need non-technical tools in our toolkit. Fortunately, we can borrow more than enough from other fields.

In this talk, I’ll cover the most tried and tested strategic data methods. They include Design Thinking, Domain-Driven Design, Value Stream Mapping, and others. For each technique, I’ll describe the motivations behind its origin, and how it has been applied through the years in different contexts. We’ll then dive deeper into practical examples from a data context. Finally, I’ll provide a template you can reuse and adjust for your situation.

To get the most out of this talk, you should be a data scientist, analyst, or engineer who works at least semi-regularly with other teams, such as marketing or product.


Attendees should have several years of experience in a product organization. Individual contributors will benefit from this talk, but ideally, they have experienced regular interactions with non-data team members (from other tech teams, product, marketing, etc.).


By getting exposure to diverse methods, attendees can conduct first sessions in their organizations. They will be able to customize the methods to the needs of their particular case. Finally, they will also be able to work more productively with members of adjacent teams, helping deliver better data-powered products for their organizations.



Boyan Angelov
Boyan Angelov is a data strategist who has spent most of his career as a management consultant and CTO, working on designing and delivering data strategies for international organizations of all scales. He has written for O’Reilly and is the author of Elements of Data Strategy: A Framework for Data and AI-Driven Transformation.




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