Overview

Raw Data is growing over time, how to manage those pr

Manage your project following Vertical Domain (Domain Driven Design)

What's the difference?

Raw Data	Insight
What you collect	What you look and feel for your business
Sits in storage	Drives decisions
Requires digging	Ready to use

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Example: Finance Department

Raw Data (What you have):

• 10,000 invoices from 2024

• Payment dates scattered across spreadsheets

• Vendor contracts in PDF folders

Insight (What you need):

• "Vendor A delivers 15 days late on average—renegotiate terms or switch suppliers"

• "Q3 cash flow drops 30% every year—prepare credit line in advance"

• "Department X consistently exceeds budget by 12%—needs spending review"

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The invoices themselves don't tell you this. But properly managed data—structured, connected, and analyzed—reveals patterns that protect your business.

DATALOG captures these insights automatically, so knowledge isn't trapped in files.

Organizing Your Data

Project

Think of Projects like sections in a university library. The science wing holds research journals, the law section contains legal references, and the business area stores financial records. Each section exists because the materials serve different purposes and require different expertise to navigate.

DATALOG uses the same principle. By organizing data into Projects, you separate information by business domain, purpose, or complexity. This separation isn't just for human convenience—it helps AI agents explore and understand your company's knowledge faster and more accurately.

Why Projects matter:

• Clear boundaries between business domains

• Agents search within relevant context, not across unrelated data

• Teams manage permissions at the project level

• Complex domains stay isolated from simpler operational data

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Import Data

Now you can