Top-Down or Bottom-Up?

What's the Right Approach to Data Products?

Which approach delivers the most value when building data products?

๐Ÿ”ผ Top-Down: Start with the business use case first. Define the problem before doing any data work. Once clear, find and package only the data you need.

๐Ÿ”ฝ Bottom-Up: Spend time modeling everything upfront, aiming to create a universal data layer. Then, when a use case emerges, see if the pre-built data model fits.

If you've been in data for a while, youโ€™ve seen the second approach play out.

๐Ÿ“Œ Massive data modeling efforts before proving value

๐Ÿ“Œ Expensive central data platforms that take years before being useful

๐Ÿ“Œ AI & analytics teams constantly fighting for access to raw data

Most organizations still operate bottom-up, despite the friction and inefficiencies.

But in today's AI-first, Agentic world, the old approach doesnโ€™t scale.


Why We Work Top-Down

In AI & Agentic workflows, iteration and raw data access are critical.

โœ… Business-first thinking ensures value is delivered fast
โœ… AI needs continuous pattern analysis, training, and new data sources
โœ… Avoids wasted effort on pre-modeling data that may never be used
โœ… Faster delivery with just the right amount of control
โœ… Greater business agility and cost reduction


The Enterprise Shift: From "Data-Centric" to "Business Process-Centric" Thinking

Instead of forcing static, pre-modeled data into ever-changing use cases, we let business processes dictate the data needs.

๐Ÿ“ We use Data Object Graphs (DOGs) to dynamically assemble the required data for each use case.
๐Ÿ“ No more waiting for the "perfect" data modelโ€”just the right data at the right time.
๐Ÿ“ AI & Agentic models thrive in this approach, adapting dynamically as business needs evolve.

This isn't just theoryโ€”this is how leading organizations are winning with AI today.


Whatโ€™s Your Approach?

Are you still stuck in bottom-up data modeling loops, or have you moved to business-first, dynamic data assembly?

Get in touch with Dataception if you want to explore a faster, more scalable approach to data products.


With Dataception's DOGs (Data Object Graphs), AI is just a walk in the park.