Idera ER/Studio Professional Edition Data Modeling Software for the Enterprise

A Full Suite of Database Tools for Data Architecture Professionals Working in a Team

Everything you need for big data modeling, all in a single user-friendly interface

Data modelers and architects are tasked with the mission-critical task of taking requirements for data assets and translating those into implementable designs. This has to be with control and within a data governance framework. Whether you are creating a new model from a conceptual model or modifying an existing asset by making changes to reverse-engineered model, user-friendly data architecture and design tools make the following tasks quicker, easier, more accurate, and more collaborative:

Floating
  • Building out an enterprise data model as entity relationship diagrams (ERD)
  • Discovering and documenting your existing data assets
  • Designing database schema, starting from logical data models through to linked physical data models
  • Laying the foundation for robust data governance and data management
  • Extensive Database Platform Support

    Access and manage models for multiple relational and big data platforms, both on premises and in the cloud. Extensive platform support is enabled through native and database-specific ODBC connections.

  • 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 Standardization

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

  • Advanced Compare and Merge

    Enable advanced, bidirectional comparisons and merges of model 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 high-quality data standards by validating for missing object definitions, unused domains, identical indexes and circular relationships.

  • 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.

  • Data Classification

    Categorize and label objects according to the level of security and privacy.

  • Permission Management

    Enable user, role and group permissions at the 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.

  • 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.

  • 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.

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Frequently-Asked Questions

Database modeling tools streamline and improve the process of creating a data model, also called a logical database structure, offering robust functionality to support SQL scripts, provide code automation, offer consistency across databases and models, and perform impact analyses on changes at the database level. There are open-source data modeling tools, but they generally don't offer the robust functionality and high-quality user experience required by most modern enterprises.

Idera’s ER/Studio facilitates seamless collaboration among stakeholders across an organization, particularly due to the model repository, which allows for robust version control and agile change management across a team.

Data modeling allows organizations to translate business requirements and knowledge into an organized conceptual data model, forming the cornerstone of business intelligence (BI). Clearly-modeled data enables organizations to make informed decisions and knowledgeable predictions.

The Model Repository for ER/Studio Data Architect Professional provides modelers with real-time collaboration features for sharing and re-using assets across data modeling projects. ER/Studio Data Architect users can connect to the same repository to work on models simultaneously and leverage features including an enterprise data dictionary (EDD), version control, and change management. Repository-based collaborative modeling provides modeling teams significant advantages, including:

  • Controlled access to data models and projects in a collaborative environment
  • Ability to display, access, and reuse common elements across models
  • Granular check-out and check-in of diagrams, sub-models, and objects
  • Conflict resolution at check-in to eliminate model differences
  • Alignment of modeling changes to development tasks and workflows
  • Clear and effective change tracking and audit trail for compliance
  • Version management for objects and models with named releases
  • Secure access to all assets to maintain data model integrity and privacy

A "good" data model is one that can be easily consumed, is scalable, provides reliably predictable performance, and is agile, able to adapt to changes in requirements.

A data model in SQL is a means of organizing and representing data stored in a SQL database, such as SQLite, SqlDBM, PostgreSQL, or Microsoft SQL Server. Data models ensure consistency in naming conventions, security, and semantics, making it easier to ensure data quality and more intuitive to work with the data.

ER/Studio Data Architect Professional Product Benefits

Document, design, and communicate data assets faster and easier

Round-trip database support gives ER/Studio Data Architect users the power to easily reverse- and forward-engineer, compare and merge, and visually document data assets across multiple relational, NoSQL, and ETL platforms and data sources. Built-in facilities automate routine data modeling tasks so users can analyze and optimize database and data warehouse designs faster than ever.

Group multiple entities aligned to a specific area into a Business Data Object

Create Business Data Objects by assigning one or more related entities to a BDO. Then, users can easily view attributes, definitions, or other information about the entities in the objects. These BDOs are then reusable objects that can be used in other submodels within the model. Users can quickly expand or collapse a Business Data Object (BDO) to simplify the model view for different end users and audiences.

Streamline collaboration on data models in a team environment through a shared repository

The Repository (included with ER/Studio Data Architect Professional) provides a secure and scalable environment for model and object version management and change management. Data modeling teams can check-out and check-in portions of the same model to work collaboratively within the repository, and easily identify which model objects have been checked in using the model explorer tree.

Easily compare differences between two data models or databases, and merge changes between them

ER/Studio Data Architect’s Compare and Merge wizard helps you reduce duplication and risk associated with multiple data sources and platforms. Quickly compare data models and databases to identify differences, and determine whether to merge differences to the source or the target. ER/Studio generates the Alter scripts to implement the changes for a database.

Manage and track model changes against user stories or tasks

In ER/Studio Data Architect Professional, data modelers can create change records to represent user stories or tasks aligned to the development workflow, and then associate them to models stored in the Repository. Object check-in and check-out within the Repository can be linked to a specific change record stored in the Change Management Center.

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