Microsoft Azure Data Catalog

Data Monitoring and Administration

Dashboards and alerts for monitoring metadata health, data pipeline status, error detection, and systematic review of data asset quality.

APIs and Integration

Open APIs and pre-built connectors for integrating with databases, cloud platforms, BI tools, and third-party systems across the data ecosystem.

Business Rules and Event Management

Configurable business rules engine with rule library for defining, managing, and enforcing data policies, validations, and quality checks.

Collaborative Workflows

Shared workspaces, commenting, task assignment, and notification features that enable team-based metadata stewardship and governance workflows.

Data Lineage

Visual and technical mapping of data from source to consumption, including all transformations, movements, and dependencies along the data flow path.

Business Context Enrichment

Annotate data assets with business context including ownership, purpose, third-party relationships, and domain-specific attributes for richer understanding.

Business Glossary

Centralized repository of business terms, definitions, and usage guidelines that standardizes data vocabulary across the organization.

Hierarchy Management

Create, manage, and apply taxonomies, hierarchies, and organizational classifications to structure metadata and enable consistent categorization.

Automated Metadata Ingestion

Automated scanning, harvesting, and enrichment of metadata from connected data sources using rules, schedules, and pattern-based extraction.

Metadata Schema Management

Define and maintain an organization-wide metadata schema, including custom attributes, tag structures, and classification hierarchies.

Quality of Features

Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Usability and Intuitiveness

End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Ease of Implementation

Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Breadth of Features

Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Business Value Created

Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Product Strategy and Rate of Improvement

Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of Data Integration

Use this data to determine whether the product will cause headaches or make data integration easy.

Vendor Support

The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Availability and Quality of Training

Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Ease of IT Administration

This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Ease of Customization

Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.