Data Modeling for Multi-Platform Environments
OverView
- Create effective data models to build a business-driven data architecture
- Document and enhance existing databases to reduce redundancy
- Implement naming standards to improve data consistency and quality
- Effectively share and manage data models across the enterprise
- Map data sources and trace origins to enhance data lineage
Design Effective Data Models
Data modeling helps organizations make better business decisions with accurately interpreted and rapidly changing data. Whether you are creating a new model from a conceptual diagram or reverse-engineering from an existing database, IDERA ER/Studio Data Architect is a powerful tool that helps you easily and effectively design and manage your logical and physical data models.
Build a Business-driven Data Architecture
Data architects need to ensure that everyone in the organization understands what the data is and can explain it in business terms. Data Architect provides an easy-to-use visual interface for data modeling professionals to document, understand, and publish information about data models and databases so they can be better harnessed to support business objectives.
Reduce Redundancy
Import and reverse-engineer content from multiple data sources into logical and physical data models, and integrate the elements into reusable constructs with an enterprise data dictionary. Leverage rich text editing along with relationship color inheritance to enhance model content and appearance.
Improve Data Consistency and Quality
Assign a naming standards template to your model, submodel, entities, and attributes. Those naming standards will be applied automatically between the logical and physical models, simplifying the data modeling process and ensuring consistency between models.
Share and Manage Enterprise Data Models
The multi-level design layers in ER/Studio Data Architect allow for the accurate visualization of data, which promotes communication between business and technical users. Manage model version control and share data assets in the repository. Create and track tasks and view changes to data models aligned to agile workflows.
Enhance Data Lineage
Universal mappings provide links between instances of the same concept across models and databases to enhance traceability even further, and data lineage shows the connections between databases, models, metadata, and data sources for traceability. Organizations can obtain a clear understanding of where their data originated, where it is used, and what the data actually means.
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