Trying to explain data modeling to non-technical stakeholders?
When explaining data modeling, it's crucial to make the concepts accessible and engaging. Here are some effective strategies:
How do you simplify technical concepts for non-technical audiences?
Trying to explain data modeling to non-technical stakeholders?
When explaining data modeling, it's crucial to make the concepts accessible and engaging. Here are some effective strategies:
How do you simplify technical concepts for non-technical audiences?
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Data modeling is like an architectural blueprint of data. The way blueprint of a building ensures all components fits together and functions properly, data modeling organizes and shows how data is connected and supports business needs. For example if you are analyzing client relationships, data modeling defines clear categories like client profiles, interactions and maps how they are related to each other.
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When presenting data models to business stakeholders, start with their business processes rather than technical details. Ask them to walk through their core workflows - this creates natural openings to explain how data modeling connects their processes. Avoid technical terms like "entities" or "cardinality" - use business language like "business units" and "connections." When explaining detail levels, relate it to their decision-making hierarchy. Tips: - Start with their process, not your data model - Use their business language, avoid jargon - Explain through workflow, not diagrams - Focus on business outcomes and decisions - Only detail when asked Remember: Your goal isn't to teach data modeling. Help them to enable business outcomes.
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When you have a lot of data it's like having a lot of plums. Sure, you can eat some and it's nice for a while, but they get stale quickly and there's not much you can do with it. But! Plums can change form into rakija and rakija gets only better over time and you can do so much with it. That's why real analysts do data modeling. And drink rakija.
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Data modeling is the process of structuring and organizing data in a way that reflects the business needs and supports efficient reporting and analysis. It’s like creating a blueprint for how data flows and relates within the organization.
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To explain data modelling to stakeholders i would simply cut out the technical jargon and focus on explaining the business value delivered by good data modelling. Some of the perceived business benefits of data modelling are a single source of truth avoiding confusion on numbers and other metrics across departments and easier and intuitive business reports. A good data model could give even business users an understanding on the data giving them the confidence to build reports on their own using tools like power bi or tableau.
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