Models, sources, tests, and documentation in dbt. The transformation layer that makes your data warehouse reliable, testable, and understandable by the whole team.
~1 hourIntermediateHands-onPrecision AI Academy
Today's Objective
Models, sources, tests, and documentation in dbt. The transformation layer that makes your data warehouse reliable, testable, and understandable by the whole team.
01
What You'll Cover Today
Day 4 of Data Modeling in 5 Days pushes into advanced territory. You have enough foundation now to tackle real-world complexity. Today's exercise is more open-ended than earlier days — that's intentional.
ℹ️
Topics today: document model, adjacency list, time-series. Each section has code you can copy and run immediately.
02
document model
Understanding document model is the core goal of Day 4. The concept is straightforward once you see it in practice — most confusion comes from skipping the mental model and jumping straight to implementation. Start with the model, then write the code.
document model
# document model — Working Example
# Study this pattern carefully before writing your own version
class documentmodelExample:
"""
Demonstrates core document model concepts.
Replace placeholder values with your real implementation.
"""
def __init__(self, config: dict):
self.config = config
self._validate()
def _validate(self):
required = ['name', 'type']
for field in required:
if field not in self.config:
raise ValueError(f"Missing required field: {field}")
def process(self) -> dict:
# Core logic goes here
result = {
'status': 'success',
'topic': 'document model',
'data': self.config
}
return result
# Usage
example = documentmodelExample({
'name': 'my-implementation',
'type': 'document model'
})
output = example.process()
print(output)
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Key insight: When working with document model, always start with the simplest possible case that works end-to-end. Complexity is easier to add than simplicity is to recover.
03
adjacency list
adjacency list is the practical application of document model in real projects. Once you understand the underlying model, adjacency list becomes the natural next step.
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Pro tip: When working with adjacency list, always read the official documentation for the exact version you're using. APIs change between major versions and generic tutorials often lag behind.
04
time-series
time-series rounds out today's lesson. It connects document model and adjacency list into a complete picture. You'll use all three concepts together in the exercise below.
05
Common Mistakes on Day 4
Skipping the fundamentals — document model requires understanding the underlying model before you can apply it correctly. Read the section twice if needed.
Ignoring error messages — error messages for adjacency list are usually precise. Read them carefully before searching online.
Hard-coding values — anything that might change between environments belongs in configuration, not in your source code.
Not testing edge cases — the happy path is not enough. What happens with empty input? With unexpected types? With network failures?
📝 Day 4 Exercise
NoSQL Patterns — Hands-On
Set up your environment for today's topic: install required tools and verify the basics work before writing any logic.
Implement a minimal working version of document model using the code example in this lesson as your starting point.
Extend your implementation to incorporate adjacency list — this is where the two concepts connect.
Test your implementation with both valid and invalid inputs. What happens at the boundaries?
Review your code: is there anything you'd name differently? Any function doing more than one thing? Refactor one thing.
Day 4 Summary
document model is the foundation of today's lesson — understand it before moving on.
adjacency list is how you apply it in real projects.
time-series ties the day's concepts together into a complete pattern.
Error handling and input validation belong in the first version, not as an afterthought.
Read error messages carefully — they usually tell you exactly what's wrong.
Challenge
Extend today's exercise by adding one feature that wasn't in the instructions. Document what you built in a comment at the top of the file. This habit of going one step further is what separates engineers who grow fast from those who stay stuck.
The foundations from today carry directly into Day 5. In the next session the focus shifts to Data Vault and Enterprise Modeling — building directly on everything covered here.