How to measure how much data one can effectively process or understand?

Question

Is there a scale of how much data one can effectively process, something similar to the "Kardashev scale for data"? What would be a name for such a thing? During Memgraph's Community Call (https://youtu.be/ygr8yvIouZk?t=1307), the point is that AgenticRuntimes + GraphRAG moves you up on the "Kardashev scale for data" because you suddenly can get much more insight from any dataset, and everyone can use it (a large corporation does not control it). I found something similar under https://adamdrake.com/from-enterprise-decentralization-to-tokenization-and-beyond.html#productize, but the definition/example looks very narrow.

mbuda · Accepted Answer

Here are clickable links: https://youtu.be/ygr8yvIouZk?t=1307, https://adamdrake.com/from-enterprise-decentralization-to-to...

kellkell · Answer

The Kardashev scale measures energy control, not information processing. If we were to define a “Kardashev scale for data,” it wouldn’t be about raw volume, but about effective abstraction capacity.
Humans don’t process data directly — we process compressed representations. So a meaningful scale would measure:
1- Throughput — how much structured data an agent can analyze per unit time.
2- Compression efficiency — how much insight is extracted per unit of data.
3- Relational depth — how many meaningful relationships can be modeled simultaneously.
Tools like Agentic Runtimes + GraphRAG don’t just increase data volume access — they expand relational modeling capacity and contextual memory. In that sense, they move users up a scale of informational leverage, not just scale of data.

mikewarot · Answer

The limiting factor would be the density of information in the source material, followed my the cognitive impedance match of the receiver.Fir example, a correct grand unified theory isn't useful if you don't know the physics to understand it.

allinonetools_ · Answer

Interesting question. In practice, I&rsquo;ve found the limit isn&rsquo;t how much data exists but how much you can turn into action without friction. The clearer and faster the feedback loop, the more data you can effectively &ldquo;use,&rdquo; regardless of volume.

rgavuliak · Answer

I would measure data by time to action. If you're not actioning data it's worthless.

How to measure how much data one can effectively process or understand?

Here are clickable links: https://youtu.be/ygr8yvIouZk?t=1307, https://adamdrake.com/from-enterprise-decentralization-to-to...

The limiting factor would be the density of information in the source material, followed my the cognitive impedance match of the receiver.
Fir example, a correct grand unified theory isn't useful if you don't know the physics to understand it.

Interesting question. In practice, I’ve found the limit isn’t how much data exists but how much you can turn into action without friction. The clearer and faster the feedback loop, the more data you can effectively “use,” regardless of volume.

I would measure data by time to action. If you're not actioning data it's worthless.