Data Quality Architecture: Threshold 63

Scenario

You are a data professional working with manufacturing data. Prepare a reliable result from machine_runs for a review.

Question

Design a source-to-report path for machine_runs. Keep records where units is at least 63, store them in machine_runs_trusted_1, and include an owner and an access rule.

Your task

Inspect the provided data and column names
Design a source-to-report path for machine_runs. Keep records where units is at least 63, store them in machine_runs_trusted_1, and include an owner and an access rule.
Run your code and compare the result

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1. Choose your dataset

Pick an industry and a size. Your code and results change to match.

IndustrySize

📓 DataPro notebookextension-data-architecture-manufacturing-intermediate-data-architecture__manufacturing__Intermediate-1.ipynbFileEditViewRunKernel: Python 3

[md]

Data Quality Architecture: Threshold 63

Design a source-to-report path for machine_runs. Keep records where units is at least 63, store them in machine_runs_trusted_1, and include an owner and an access rule.

In [1]:

Your code cell is below. Press Check my answer to run the cell — the result appears as Out [1].

python editormachine_runs

Snippets

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🌈 In short — no coding words

📂 Opens the "machine_runs" table→✅ Shows you the answer

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Dataset & schema

machine_runs

IndustryDataset size

The tiny starter data. Bigger data scrolls.

Fields

run_id	line	units
R1	LineA	120
R2	LineB	80
R3	LineA	150
R4	LineC	60

Manufacturing practice data only.

attempts: 0

▶ Output terminal

$ Press “Check my answer” — results appear here.

Your next steps

Each item turns green when your answer includes it.

5 left

Names the source
Defines the quality rule
Names trusted storage
Defines access
Names governance