| 01Automated Metadata Discovery & Harvesting |
Scans connected systems to collect technical metadata such as schemas, tables, columns, files, reports, pipelines, and other data assets. |
Connect Data Sources→
Scan Systems→
Extract Technical Metadata→
Populate Metadata Repository
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Coverage for databases, warehouses, BI tools, ETL, and cloud platforms
Scheduled and incremental metadata scans
Automatic detection of new or changed data assets
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| 02Enterprise Data Catalog |
Creates a searchable inventory of datasets, tables, dashboards, reports, models, files, and other information assets across the organization. |
Ingest Metadata→
Organize Data Assets→
Index for Search→
Browse & Discover Assets
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Search across technical and business metadata
Facets, filters, tags, domains, and asset classifications
Support for datasets, reports, dashboards, models, and pipelines
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| 03Business Glossary & Data Definitions |
Standardizes business terms, definitions, acronyms, policies, and ownership so teams use consistent language when working with enterprise data. |
Create Business Term→
Define Meaning & Owner→
Link to Data Assets→
Publish Approved Definition
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Term ownership, stewardship, approval, and versioning
Links between business terms and technical assets
Synonyms, acronyms, classifications, and policy references
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| 04Data Lineage & Impact Analysis |
Shows how data moves and transforms from source systems through pipelines, models, warehouses, reports, and downstream applications. |
Capture Source & Transformation Metadata→
Map Data Relationships→
Visualize End-to-End Lineage→
Assess Change Impact
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Column-, table-, report-, and pipeline-level lineage
Automated parsing of SQL, ETL, and transformation logic
Upstream and downstream impact analysis before changes
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| 05Metadata Classification & Tagging |
Labels data assets by business domain, sensitivity, content type, regulatory relevance, ownership, and other organizational categories. |
Scan Data Asset→
Detect Metadata / Content Pattern→
Apply Tag or Classification→
Use in Search & Governance
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Manual and automated classification rules
Sensitive, personal, financial, or regulated-data tagging
Custom taxonomies and business-domain classifications
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| 06Metadata Stewardship & Governance Workflows |
Assigns responsibility for metadata quality, definitions, classifications, approvals, and issue resolution to designated data owners and stewards. |
Create Metadata Change / Issue→
Route to Steward→
Review & Approve→
Publish Governed Metadata
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Owner and steward assignment by asset or domain
Approval, certification, review, and escalation workflows
Comments, tasks, issue queues, and accountability history
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| 07Metadata Relationships & Knowledge Graph |
Connects datasets, business terms, systems, reports, owners, policies, processes, and other assets to show how information is related across the organization. |
Collect Metadata Entities→
Identify Relationships→
Build Connected Metadata Graph→
Explore Data Context
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Relationships across technical, business, and operational metadata
Visual graph navigation and dependency exploration
Custom relationship types and domain models
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| 08Data Quality Context & Asset Certification |
Links quality indicators, validation results, trust status, freshness, and certification information with metadata so users can judge whether an asset is suitable for use. |
Collect Quality & Freshness Signals→
Link Metrics to Data Asset→
Review Trust Criteria→
Certify / Flag Asset
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Data quality scores, freshness, and issue indicators
Trusted, certified, deprecated, or draft asset statuses
Integration with data quality and observability platforms
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| 09Metadata Search, Collaboration & Usage Insights |
Helps users find relevant data faster and understand who uses it, how often it is accessed, and what business context or feedback exists around each asset. |
Search Metadata Catalog→
Review Context & Usage→
Ask / Comment / Endorse→
Select Trusted Data Asset
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Natural-language, keyword, and faceted search
Comments, ratings, endorsements, and expert identification
Popularity, query, usage, and recent-activity signals
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| 10Metadata Analytics & Platform Integrations |
Measures catalog adoption, governance coverage, lineage completeness, metadata quality, and stewardship activity while connecting metadata with the broader data stack. |
Aggregate Metadata Activity→
Analyze Governance & Catalog KPIs→
Connect Enterprise Data Platforms→
Improve Metadata Coverage
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Catalog adoption, stewardship, classification, and lineage dashboards
Data warehouse, lakehouse, BI, ETL, governance, and observability integrations
APIs, metadata exchange, exports, and automated synchronization
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