Enterprise data management
Eliminate data silos and unlock the information advantage
Data is an organization’s most valuable resource, but only when harnessed and leveraged effectively. With increasing data volumes, fragmented enterprise application landscapes and a growing variety of data types, many organizations struggle to manage data quality. Enterprise data management delivers insights and new sources of competitive differentiation from data to help control costs, understand customers and improve the bottom line.
OpenText enterprise data management solutions address a broad range of data management needs, from data governance and data quality to data security and more. Using OpenText™ Alloy™ for enterprise data management, organizations move beyond basic integration and turn data into insights and action.
What is enterprise data management?
Enterprise data management addresses the critical aspects of managing data across the enterprise from multiple source systems, including data originating outside of the organization. It mitigates data conflicts and quality inconsistencies and is critical to ensuring timely and secure access to consolidated, clean and accurate data.
Enterprise data management represents an evolution from traditional master data management (MDM) solutions, which focus solely on customer and product information management. While important, master data is just one aspect of enterprise data management. All aspects of an enterprise’s data lifecycle, from storage to security to quality assurance and beyond, must be managed. The best enterprise data management solutions combine all forms of data integration and data management in a single cloud platform.
OpenText Alloy data management overview
Alloy enables organizations to harmonize, cleanse, enrich and aggregate data in a single cloud platform to improve process automation and efficiency. Alloy offers deeper insights into operations by enabling various types of materialized views to be built on reliable data using any business intelligence tool.
Built on the OpenText Cloud, Alloy natively supports the storage, integration and syndication activities required to supply quality data to the enterprise. The platform offers the flexibility to customize solutions to align with unique data strategies and evolving requirements.
OpenText Alloy data management features
Validates data against business rules, reference data and other sources, such as third-party data validation services, to improve data quality across the enterprise.
Standardizes data from multiple sources to provide aggregated views efficiently and automatically.
Builds materialized views of data on a selection of database types, including graph, search, key/value, document and relational databases, and can use any analytics/BI tool to visualize data for optimal analytics performance.
Flexible data modeling
Creates new data models based on changing business needs. Stores data in an immutable log that enables new data models to be applied to historical data.
Leverages the scalability of the OpenText Cloud to adapt to new and more diverse data and analytics capabilities.
Offers the technical and business expertise of OpenText data professionals to design and operate data management solutions that align strategy with optimal support.
OpenText Alloy Data Management benefits
Accelerate digital transformation initiatives
Remove the technical hurdles of digital transformation, improve efficiency of business processes and tailor solutions to optimally meet evolving business requirements.
Gain 360-degree visibility
Break down data silos with integration and data management for a unified view of enterprise data across different applications and systems.
Improve data quality and optimize delivery using the right data models, materialized views and data preparation capabilities. Mitigate business risks and identify new business opportunities with data that executives can trust.
Speed time to market
Get faster value from data by extending internal IT resources with OpenText experts to scale up delivery capabilities for data management projects.
Reduce the costs of bad data
Automate manual data cleaning processes to improve efficiency of data preparation tasks and reduce the amount of errors and business process inefficiencies caused by poor data quality.
Strengthen data compliance and security
Maintain and improve data security and compliance with applicable standards by leveraging the secure OpenText Cloud platform.