microsoft-purview-and-azure-data-governance

Name: microsoft-purview-and-azure-data-governance
Author: vaquarkhan

19stars4forks

How to install microsoft-purview-and-azure-data-governance?

vaquarkhan/data-engineering-agent-skills/microsoft-purview-and-azure-data-governance

$npx -y skills add vaquarkhan/data-engineering-agent-skills --skill microsoft-purview-and-azure-data-governance

Installs into the current project.

Summary

Guides agents through Microsoft Purview and Azure-native data governance workflows. Use when designing collections, scans, classifications, lineage, policy boundaries, and governed publishing across ADLS, Synapse, Data Factory, Azure Databricks, Fabric, and Azure analytics estate

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SKILL.md

1	# Microsoft Purview And Azure Data Governance
2
3	## Overview
4
5	Use this skill when `Microsoft Purview` is the governance control plane for `Azure` data platforms. It helps agents design metadata collections, classification strategy, scan scope, lineage expectations, and governed publish behavior across Microsoft analytics surfaces.
6
7	## When to Use
8
9	- designing `Purview` collection and ownership structure
10	- defining scans, classifications, glossary, and lineage expectations
11	- governing datasets across `ADLS`, `Synapse`, `Data Factory`, `Azure Databricks`, or `Fabric`
12	- improving trusted discovery and certification for shared data products
13	- aligning Azure-native governance with privacy, security, and release controls
14
15	Do not assume `Purview` is only a catalog tool. It often becomes the platform evidence and policy surface for governed analytics.
16
17	## Workflow
18
19	1. Define governance scope.
20	Clarify:
21	- in-scope platforms
22	- business domains
23	- critical data products
24	- stewardship and ownership model
25
26	2. Design the metadata operating model.
27	Decide:
28	- collections
29	- glossary boundaries
30	- classifications and sensitivity labels
31	- scan cadence and ownership
32
33	3. Define trusted publish behavior.
34	Require:
35	- certification or endorsement rules
36	- lineage completeness expectations
37	- ownership visibility
38	- ties to regulated-data controls where relevant
39
40	4. Align Azure services with governance.
41	Check how `Purview` works with `ADLS`, `Synapse`, `Data Factory`, `Databricks`, and `Fabric` rather than treating each system separately.
42
43	5. Validate operational sustainability.
44	Make sure scans, classifications, and lineage remain useful as assets, teams, and environments grow.
45
46	## Common Rationalizations
47
48	\| Rationalization \| Reality \|
49	\| --- \| --- \|
50	\| "Scanning everything is the same as governing it." \| Governance also needs ownership, trust signals, and useful boundaries for consumers. \|
51	\| "Purview can be added after pipelines are done." \| Late governance usually means weak lineage, poor certification, and inconsistent discovery. \|
52	\| "Each Azure service team can manage metadata separately." \| Fragmented governance weakens platform-wide trust and policy evidence. \|
53
54	## Red Flags
55
56	- collections do not map to real ownership or domains
57	- scan scope is broad but lineage and certification are weak
58	- classifications are inconsistent across Azure services
59	- `Purview` is disconnected from publish or security decisions
60	- stewardship expectations depend on tribal knowledge
61
62	## Verification
63
64	- [ ] Governance scope and stewardship model are explicit
65	- [ ] Collections, scans, and classifications are intentionally designed
66	- [ ] Trusted publish behavior includes lineage and certification expectations
67	- [ ] Azure services align to one governance model
68	- [ ] The model stays sustainable as adoption grows

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microsoft-purview-and-azure-data-governance

19stars4forks

View on GitHub

How to install microsoft-purview-and-azure-data-governance?

vaquarkhan/data-engineering-agent-skills/microsoft-purview-and-azure-data-governance

$npx -y skills add vaquarkhan/data-engineering-agent-skills --skill microsoft-purview-and-azure-data-governance

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Microsoft Purview And Azure Data Governance
2
3	## Overview
4
5	Use this skill when `Microsoft Purview` is the governance control plane for `Azure` data platforms. It helps agents design metadata collections, classification strategy, scan scope, lineage expectations, and governed publish behavior across Microsoft analytics surfaces.
6
7	## When to Use
8
9	- designing `Purview` collection and ownership structure
10	- defining scans, classifications, glossary, and lineage expectations
11	- governing datasets across `ADLS`, `Synapse`, `Data Factory`, `Azure Databricks`, or `Fabric`
12	- improving trusted discovery and certification for shared data products
13	- aligning Azure-native governance with privacy, security, and release controls
14
15	Do not assume `Purview` is only a catalog tool. It often becomes the platform evidence and policy surface for governed analytics.
16
17	## Workflow
18
19	1. Define governance scope.
20	Clarify:
21	- in-scope platforms
22	- business domains
23	- critical data products
24	- stewardship and ownership model
25
26	2. Design the metadata operating model.
27	Decide:
28	- collections
29	- glossary boundaries
30	- classifications and sensitivity labels
31	- scan cadence and ownership
32
33	3. Define trusted publish behavior.
34	Require:
35	- certification or endorsement rules
36	- lineage completeness expectations
37	- ownership visibility
38	- ties to regulated-data controls where relevant
39
40	4. Align Azure services with governance.
41	Check how `Purview` works with `ADLS`, `Synapse`, `Data Factory`, `Databricks`, and `Fabric` rather than treating each system separately.
42
43	5. Validate operational sustainability.
44	Make sure scans, classifications, and lineage remain useful as assets, teams, and environments grow.
45
46	## Common Rationalizations
47
48	\| Rationalization \| Reality \|
49	\| --- \| --- \|
50	\| "Scanning everything is the same as governing it." \| Governance also needs ownership, trust signals, and useful boundaries for consumers. \|
51	\| "Purview can be added after pipelines are done." \| Late governance usually means weak lineage, poor certification, and inconsistent discovery. \|
52	\| "Each Azure service team can manage metadata separately." \| Fragmented governance weakens platform-wide trust and policy evidence. \|
53
54	## Red Flags
55
56	- collections do not map to real ownership or domains
57	- scan scope is broad but lineage and certification are weak
58	- classifications are inconsistent across Azure services
59	- `Purview` is disconnected from publish or security decisions
60	- stewardship expectations depend on tribal knowledge
61
62	## Verification
63
64	- [ ] Governance scope and stewardship model are explicit
65	- [ ] Collections, scans, and classifications are intentionally designed
66	- [ ] Trusted publish behavior includes lineage and certification expectations
67	- [ ] Azure services align to one governance model
68	- [ ] The model stays sustainable as adoption grows

People who liked this also viewed

6 picks

Type