IBM InfoSphere Master Data Management
IBM InfoSphere Master Data Management is a platform that helps organizations gain control over their critical data assets. It provides data governance, stewardship, and integration capabilities to help ensure data is complete, consistent, and accurate across the enterprise.
data-governance
data-integration
master-data-management
data-quality
IBM InfoSphere Master Data Management
A platform for gaining control over critical data assets, providing data governance, stewardship, and integration capabilities.
What is IBM InfoSphere Master Data Management?
IBM InfoSphere Master Data Management (MDM) is a comprehensive platform designed to help organizations gain greater control over their critical data assets. It provides a centralized architecture along with data governance, stewardship, and integration capabilities to help ensure high data quality and accessibility.
Key capabilities of IBM InfoSphere MDM include:
- Centralized master data hub - Provides a single trusted view of master data domains like customers, products, suppliers etc.
- Data governance - Manage data policies, standards, roles and business rules.
- Data stewardship - Manage data issue tracking, collaboration and workflow.
- Hierarchical data modeling - Define data relationships and hierarchies.
- Matching and merging - Identify duplicate data and merge it.
- Data quality and validation - Ensure data accuracy and completeness.
- Workflow and process management - Model data management processes.
- packaged for industries like product information management, customer data integration etc.
By providing robust master data management capabilities on a single integrated platform, InfoSphere MDM aims to help organizations achieve a single view of the truth for their business-critical data. This can enable data-driven business benefits such as improved operational efficiency, deeper customer insight and better regulatory compliance.
IBM InfoSphere Master Data Management Features
Features
- Master data management
- Data integration
- Data quality
- Data governance
- Metadata management
- Data stewardship
Pricing
- Subscription-Based
- Pay-As-You-Go
Pros
Integrates data from multiple sources
Provides a single source of truth for master data
Improves data quality
Enables data governance and stewardship
Scalable architecture
Cons
Complex implementation
Requires significant investment and expertise
Limited support for unstructured data
Steep learning curve
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