Analysis & Design


Idera ER/Studio Data Architect

Idera ER/Studio Data Architect boxshot.

Idera ER/Studio Data Architect

Published By:  Embarcadero

Model and analyse your enterpirse data landscape for business value

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ER/Studio Data Architect gives users the power to easily reverse- and forward-engineer, compare and merge, and visually document data assets across multiple platforms and data sources. ER/Studio enables data professionals to better manage data models and metadata in complex and dynamic enterprise environments.

ER/Studio Data Architect documents and enhances existing databases, improves data consistency and quality, and effectively communicates models across
the enterprise. A variety of database platforms, including traditional RDBMS,
cloud databases on Azure, and big data technologies such as MongoDB and
Hadoop Hive, can be imported and integrated into shared models and metadata
glossaries. ER/Studio Data Architect includes the import bridges for common
modeling tools, to easily migrate their native formats into ER/Studio.

  • 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

Enterprise Model Management

Forward and Reverse Engineering

Generate physical data models from existing database designs. Construct graphical models from existing database or schema, for both relational and big data platforms. Easily apply design changes with formulated alter code

Universal Mappings

Map between and within conceptual, logical and physical model objects to trace objects upstream or downstream, using the repository, and specify metadata such as definitions, notes, and attachments

Data Dictionary Standardisation

Define and enforce standard data elements, naming standards and reference values for use across and between data models

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

Submodel Management

Allow creation of multi-leveled submodels, merge submodel properties across existing models and synchronize submodel hierarchies

Naming Standards

Assign a naming standards template to models, submodels, entities and attributes for automatic application between logical and physical models

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

Data Integration

Visual Data Lineage

Visually document source/target mapping and sourcing rules using a drag-and-drop interface to understand Extraction, Transformation, and Load (ETL) data movement across systems

Source-to-target Mapping

View the relationships between the source and target, how the data flows from one table to another, and how the data is transformed

Dimensional Modeling

Leverage complex star and snowflake schema designs and support importing rich dimensional metadata from BI and data warehouse platforms

Metadata Integration

Import and export metadata from BI Platforms, UML and data modeling solutions, XML Schemas and CWM (Common Warehouse Metamodel) to create a metadata hub

Security Management

Data Classification

Categorise and label objects according to the level of security and privacy

Permission Management

Enable user, role and group permissions at logical and physical level

Security Attributes

Define data security types and properties to be observed and enforced for compliance

Security Center Groups

Streamline security administration with local or LDAP groups improving productivity and reducing errors


Concurrent Model and Object Access

Allows real-time collaboration between modelers working on data models down to the model object level with token-based check-in/check-out

Version Management

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

Agile Change Management

Assign and track tasks associated with data models to align changes to user stories and development workflows.

Design Environment

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 normalisation and compliance with the target database

Rich Text Editing

Easily edit text in data object fields, with integrated spell-checking, embedded hyperlinks, and text wrapping.

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 Reporting Formats

Publish models and reports in a variety of formats including HTML, RTF, XML Schema, PNG, JPEG and DTD Output

The standard ER/Studio Data Architect edition provides an easy-to-use
visual interface to reverse-engineer industry-leading database systems
and allow a data modeler to compare and consolidate common data
structures without creating unnecessary duplication. Data architects can
also define Business Data Objects (BDOs) in the logical and physical
models to represent master data and transactional concepts with multiple
entities and relationships, such as products and customers. Using
industry standard notations, data modelers can create a metadata hub
by importing, analyzing, and repurposing metadata from data sources
such as business intelligence applications, ETL environments, XML
documents, and other modeling solutions.

The ER/Studio Data Architect Professional edition also includes the
model repository for version control and agile change management. Data
professionals can create task records to represent user stories or tasks
and associate them to models, keeping data models relevant and current
with fast-changing databases and applications. With a 64-bit repository,
larger data models can be processed with improved performance on key
operations such as compare and merge.

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