# Metadata Activation

## Overview

**Metadata Activation** is Euno's framework for turning passive metadata into automated actions that improve data governance, reduce manual work, and keep your data stack healthy.

Instead of just cataloging metadata, Euno lets you:

* **React automatically** when metadata changes
* **Enforce policies** through automated workflows
* **Keep systems in sync** without manual intervention
* **Get notified** about data governance issues

***

## Why Metadata Activation Matters

Most data catalogs stop at *observing* your data stack. Metadata Activation takes the next step: **doing something about it**.

### The Problem

Without Metadata Activation, your team faces:

❌ **Manual Governance Enforcement**

* Manually checking for undocumented tables
* Chasing down resource owners for descriptions
* Spreadsheets to track PII and critical data

❌ **Sync Drift Between Tools**

* BI models become outdated when dbt changes
* Analysts rebuild logic that already exists in dbt
* Inconsistent metrics across tools

❌ **Reactive Incident Response**

* Discover breaking changes after they happen
* Scramble to find downstream impacts
* No visibility into who's affected

❌ **Lost Productivity**

* Data teams spend time on repetitive tasks
* Analysts wait for central teams to make changes
* Everyone duplicates work

### The Solution

Metadata Activation helps you:

✓ **Automate Governance**

* Alert when new ungoverned resources appear
* Notify owners when resources lack documentation
* Track and propagate PII tags automatically

✓ **Keep Tools in Sync**

* Auto-update BI models when dbt changes
* Push metrics from dbt to Looker automatically
* Ensure everyone uses the same definitions

✓ **Prevent Issues Proactively**

* Get notified before making breaking changes
* Understand blast radius of proposed changes
* Alert stakeholders about upcoming impacts

✓ **Scale Data Operations**

* Reduce manual coordination overhead
* Enable self-service with guardrails
* Free data teams for higher-value work

***

## How It Works

Metadata Activation consists of three core capabilities:

### 1. **Workflows** 🔔

Define triggers based on your metadata and get notified when conditions are met.

**How it works:**

1. Write a query (using EQL) that describes what you want to monitor
2. Set a condition (e.g., "when query returns > 0 results")
3. Choose notification channels (Slack, Email)
4. Workflows run daily and notify you when triggered

**Example Use Cases:**

| Scenario                      | Workflow                                                                            |
| ----------------------------- | ----------------------------------------------------------------------------------- |
| **Governance Monitoring**     | "Notify #data-governance when new tables appear without a `domain` tag"             |
| **Documentation Enforcement** | "Alert #analytics when dbt models are created without descriptions"                 |
| **Usage Monitoring**          | "Notify dashboard owners when their dashboards haven't been viewed in 90 days"      |
| **PII Tracking**              | "Alert #security when tables with PII columns are queried by non-approved users"    |
| **Cost Management**           | "Notify #data-platform when Snowflake warehouse costs increase >20% week-over-week" |
| **Change Detection**          | "Alert #bi-team when new columns are added to certified Looker explores"            |

[Learn more about Workflows →](https://docs.euno.ai/using-euno/metadata-activation/workflows)

### 2. **Data Model Sync** 🔄

Keep your BI tools automatically in sync with your transformation logic.

**How it works:**

1. Euno detects changes in your dbt manifest
2. Automatically generates updated LookML (or other BI format)
3. Creates a pull request in your BI repository
4. Your team reviews and merges the changes

**Supported Platforms:**

* ✓ Looker (via LookML sync from dbt)
* 🔜 Tableau (coming soon)
* 🔜 Power BI (coming soon)

**Example Benefits:**

| Without Sync                                                                                                              | With Sync                                                                                                           |
| ------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------- |
| Analytics engineer adds metric in dbt → BI developer manually recreates it in Looker → 3 days later, possibly with errors | Analytics engineer adds metric in dbt → Euno auto-generates LookML → PR created automatically → Merge in 10 minutes |
| Column renamed in dbt → BI dashboards break → Scramble to fix → Users see errors                                          | Column renamed in dbt → Euno updates LookML → PR shows exactly what changed → Controlled rollout                    |
| Metrics calculated differently in dbt vs. BI → Inconsistent reports → Trust erosion                                       | Single source of truth in dbt → Always synced to BI → Consistent definitions everywhere                             |

[Learn more about Data Model Sync →](https://docs.euno.ai/using-euno/metadata-activation/data-application-sync)

### 3. **Impact Analysis** 📊

Understand the ripple effects of changes before you make them.

**How it works:**

1. Select a resource (table, column, dashboard, etc.)
2. Euno analyzes all downstream dependencies
3. Get a comprehensive report of what would be affected
4. Make informed decisions about changes

**Example Questions Answered:**

* "If I delete this table, what dashboards will break?"
* "If I change this column name, what needs to be updated?"
* "If I deprecate this dbt model, what's the blast radius?"
* "Who should I notify before making this change?"

[Learn more about Impact Analysis →](https://docs.euno.ai/using-euno/impact-analysis)

***

## Getting Started with Metadata Activation

### Step 1: Connect Your Sources

Metadata Activation works best when Euno has visibility into your entire stack:

* Connect your transformation tool (dbt)
* Connect your data warehouse (Snowflake, BigQuery)
* Connect your BI tools (Tableau, Looker)

More connections = more powerful automation.

### Step 2: Start with Workflows

Workflows are the easiest entry point. Start with these simple use cases:

**Beginner Workflow:**

```
Alert #data-team when new Snowflake tables are created
```

**Intermediate Workflow:**

```
Notify owners when dbt models haven't been updated in 90 days
```

**Advanced Workflow:**

```
Alert #governance when tables containing PII are accessed by 
non-approved roles, and the table isn't tagged as audited
```

[Create Your First Workflow →](https://docs.euno.ai/using-euno/metadata-activation/workflows)

### Step 3: Enable Data Model Sync (if applicable)

If you use dbt + Looker:

1. Configure your dbt and Looker sources
2. Set up the Data Model Sync automation
3. Run your first sync to see the generated LookML
4. Review and merge the PR

[Set Up Data Model Sync →](https://docs.euno.ai/using-euno/metadata-activation/data-application-sync)

### Step 4: Use Impact Analysis Before Changes

Before deprecating a table or changing logic:

1. Open the resource in Euno
2. Run Impact Analysis
3. Review all downstream dependencies
4. Notify affected stakeholders
5. Proceed with confidence

[Learn Impact Analysis →](https://docs.euno.ai/using-euno/impact-analysis)

***

## Real-World Examples

### Example 1: Automated Governance at Scale

**Company:** Mid-size B2B SaaS company\
**Challenge:** 500+ Snowflake tables, 40% undocumented\
**Solution:** Workflow that alerts table owners weekly about missing documentation

**Workflow Configuration:**

```
Query: Find tables without descriptions
Condition: Results > 0
Action: Send Slack message to table owner
Schedule: Every Monday at 9 AM
```

**Results:**

* Documentation rate increased from 60% → 92% in 3 months
* Reduced "what does this table do?" Slack questions by 75%
* New tables are documented within 1 week

### Example 2: dbt-to-Looker Automation

**Company:** E-commerce company\
**Challenge:** BI team spending 20 hours/week manually syncing dbt changes to Looker\
**Solution:** Data Model Sync from dbt to LookML

**Before:**

1. Analytics engineer updates dbt metric
2. Creates Jira ticket for BI team
3. BI developer recreates metric in LookML
4. Back-and-forth to verify calculation
5. 3-5 days elapsed time

**After:**

1. Analytics engineer updates dbt metric
2. Euno auto-generates LookML
3. PR created automatically with exact changes
4. BI team reviews and merges
5. 15 minutes elapsed time

**Results:**

* 90% reduction in sync time
* Zero calculation inconsistencies
* BI team can focus on complex visualizations

### Example 3: Proactive Change Management

**Company:** Financial services firm\
**Challenge:** Frequent unintended dashboard breakages from upstream changes\
**Solution:** Impact Analysis before every change + automated stakeholder notifications

**Process:**

1. Developer wants to rename a column in dbt
2. Runs Impact Analysis in Euno
3. Sees 15 downstream Tableau dashboards affected
4. Workflow automatically notifies dashboard owners
5. Coordinates change during maintenance window

**Results:**

* Zero unintended dashboard breakages in 6 months
* 95% reduction in "why is my dashboard broken?" incidents
* Improved trust between data and analytics teams

***

## Best Practices

### For Workflows

✓ **Start Small**

* Begin with simple, low-risk workflows
* Add complexity as you learn

✓ **Be Specific in Queries**

* Target exact resource types and conditions
* Avoid overly broad notifications

✓ **Choose the Right Cadence**

* Daily for governance checks
* Immediate for critical issues
* Weekly for cleanup reminders

✓ **Optimize Notification Channels**

* Use Slack for team alerts
* Use Email for individual notifications
* Create dedicated channels for workflow notifications

### For Data Model Sync

✓ **Start with a Subset**

* Sync a few models first to test
* Expand gradually as confidence grows

✓ **Use Staging Branches**

* Don't sync directly to production
* Review PRs before merging

✓ **Document Naming Conventions**

* Handle collisions consistently
* Use meta keys for custom naming

✓ **Monitor Sync Health**

* Review sync logs regularly
* Address failures quickly

### For Impact Analysis

✓ **Run Before Every Breaking Change**

* Column renames
* Table drops
* Schema changes

✓ **Document Your Findings**

* Export impact reports
* Share with stakeholders
* Track in project management tools

✓ **Communicate Early**

* Notify affected teams before changes
* Provide timeline and migration plan
* Offer support during transition

***

## Success Metrics

How to measure the impact of Metadata Activation:

### Governance Metrics

* % of resources with documentation
* % of tables with appropriate tags
* Time to document new resources

### Efficiency Metrics

* Time spent on manual sync tasks
* Number of governance-related Slack messages
* Hours saved per week on repetitive work

### Quality Metrics

* Number of dashboard breaking incidents
* Metric consistency across tools
* Data trust survey scores

### Adoption Metrics

* Number of active workflows
* % of changes using Impact Analysis
* Team satisfaction scores

***

## Limitations & Considerations

### Workflows

* Execute maximum once per day
* 60-second query timeout
* Maximum 100,000 results per query
* Requires source integrations to be active

### Data Model Sync

* Currently supports dbt → Looker only
* Requires Git access for PR creation
* Some complex dbt patterns may not sync
* Requires review before production deployment

### Impact Analysis

* Depends on connected sources
* Limited to relationships Euno can observe
* May not capture external dependencies
* Requires up-to-date metadata

***

## Next Steps

1. **Create Your First Workflow**
   * Start with a simple governance use case
   * [Workflows Guide →](https://docs.euno.ai/using-euno/metadata-activation/workflows)
2. **Explore Data Model Sync**
   * If you use dbt + Looker
   * [Data Model Sync Setup →](https://docs.euno.ai/using-euno/metadata-activation/data-application-sync)
3. **Try Impact Analysis**
   * Before your next schema change
   * [Impact Analysis Guide →](https://docs.euno.ai/using-euno/impact-analysis)
4. **Join the Community**
   * Share your automation ideas
   * Learn from other Euno users

***

## Related Documentation

* [Workflows](https://docs.euno.ai/using-euno/metadata-activation/workflows) - Automated notifications and alerts
* [Data Model Sync](https://docs.euno.ai/using-euno/metadata-activation/data-application-sync) - Keep BI tools in sync
* [Impact Analysis](https://docs.euno.ai/using-euno/impact-analysis) - Understand change impact
* [Using Euno](https://docs.euno.ai/using-euno) - Day-to-day features
* [Source Integrations](https://docs.euno.ai/sources) - Connect your data tools

***

## Questions?

* **In-App Support:** Click the chat icon
* **Email:** <support@euno.ai>
* **Documentation:** [Full Metadata Activation Docs](https://docs.euno.ai/using-euno/metadata-activation)

Ready to activate your metadata? [Start with Workflows →](https://docs.euno.ai/using-euno/metadata-activation/workflows)