ER/STUDIO DATA ARCHITECT
- Create effective 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 communicate models across the enterprise
- Map data sources and trace origins to enhance data lineage
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 to document, understand, and publish information about data models and databases so they can be better harnessed to support business objectives.
Import and reverse-engineer content from multiple data sources and integrate the elements into reusable constructs with an enterprise data dictionary. Document existing databases to allow reuse of common data elements and structures, for better support of business objectives.
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 modeling process and ensuring consistency between models. Track model changes associated with agile workflows.
Share and Communicate Across the Enterprise
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 and data lineage provide the connections between models and data sources for traceability. With a clear understanding of where data originated and where it is used, organizations can be assured that they know what their data actually means and how it can best be utilized.
ER/Studio Data Architect is available in two editions: The standard ER/Studio Data Architect edition is the feature-rich tool with extensive data modeling capabilities across multiple platforms, along with import bridges for other common modeling tools. The ER/Studio Data Architect Professional edition also includes the model repository for version control and agile change management.
Advanced Graphics and Layout
Automatically create highly readable, highly navigable diagrams with one or a combination of layouts
Automated and Custom Transformation
Streamlines the derivation of one or more physical designs from a logical one and checks for normalization and compliance with the target database
Extensible Automation Interface
Automate tedious, routine tasks such as coloring tables, enforcing and applying naming standards, globally update storage parameters and integrate with desktop applications
Multiple Presentation Formats
Publish models and reports in a variety of formats including HTML, RTF, XML Schema, PNG, JPEG and DTD Output
Visual Data Lineage
Visually document source/target mapping and sourcing rules for data movement across systems
Leverage complex star and snowflake schema designs and support importing rich dimensional metadata from BI and data warehouse platforms
Categorize and label objects according to the level of security and privacy
Enable user, role and group permissions at logical and physical level
Concurrent Model and Object Access
Allows real-time collaboration between modelers working on data models down to the model object level
Manages the individual histories of models and model objects to ensure incremental comparison between, and rollback to, desired diagrams
Component Sharing and Reuse
Predefined Enterprise Data Dictionary eliminates data redundancy and enforces data element standards
Security Center Groups
Streamline security administration with local or LDAP groups improving productivity and reducing errors
Agile Change Management
Assign and track tasks associated with data models to align changes to user stories and development workflows.
Enterprise Model Management
Forward and Reverse Engineering
Generate source code from database designs. Construct graphical models from existing database or schema. Apply design changes with formulated alter code
Map between and within conceptual, logical and physical model objects to trace objects upstream or downstream
Data Dictionary Standardization
Define and enforce standard data elements, naming standards and reference values
Advanced Compare and Merge
Enable advanced bi-directional comparisons and merges of models and database structures
Business Data Objects
Represent master data and transactional concepts with multiple entities and relationships, such as products, customers, and vendors
Allow creation of multi-leveled submodels, merge submodel properties across existing models and synchronize submodel hierarchies
Assign a naming standards template to models, submodels, entities and attributes for automatic application between logical and physical models
Import and export metadata from BI Platforms, UML and data modeling solutions, XML Schemas and CWM (Common Warehouse Metamodel) to create a metadata hub
Automatic Migration of Foreign Keys
Maintain foreign keys to ensure referential integrity in database designs
”Where Used” Analysis
Display mappings between logical entities and attributes to their implementation across physical designs
Model Completion Validation
Automate model reviews and enforce standards by validating for missing object definitions, unused domains, identical indexes and circular relationships