Kalodata
Kalodata is a data governance and master data management solution that helps organizations track, manage, and optimize their critical data assets. It provides features like data cataloging, data quality, hierarchy management, and governance workflows.
data-governance
master-data-management
data-cataloging
data-quality
hierarchy-management
Kalodata: Data Governance & Master Data Management Solution
Kalodata helps organizations track, manage, and optimize critical data assets with features like data cataloging, data quality, hierarchy management, and governance workflows.
What is Kalodata?
Kalodata is a flexible and scalable master data management (MDM) software solution designed to help enterprises gain control over their business-critical data. It serves as a central hub for managing master data domains such as customers, products, suppliers, locations etc.
Key features and benefits of Kalodata include:
- Intuitive data modeler to define data hierarchies, relationships, validation rules etc.
- Powerful matching engine to consolidate duplicate data records
- Data stewardship workflows for governing data changes
- Role-based interfaces for different users - data stewards, business analysts etc.
- Embedded data quality functions for profiling, cleansing and enriching data
- Metadata management and detailed audit trails for compliance
- Pre-built integrations with ERPs, CRMs and other systems
- Cloud-native architecture that scales easily as data volumes grow
Overall, Kalodata accelerates time-to-value by providing a flexible MDM platform to govern trustworthy master data across the enterprise. Its intuitive features make it easy for businesses to gain control over their critical data assets.
Kalodata Features
Features
- Data Cataloging
- Data Quality Management
- Hierarchy Management
- Governance Workflows
- Metadata Management
- Data Lineage Tracking
- Role-Based Access Control
- Reporting and Analytics
Pricing
- Subscription-Based
Pros
Comprehensive data governance capabilities
Centralized view of data assets
Improved data quality and consistency
Streamlined data management processes
Customizable workflows and rules
Scalable and enterprise-ready
Cons
Complex implementation for large organizations
Steep learning curve for some users
Potential integration challenges with existing systems
Ongoing maintenance and support costs
Official Links
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