ER/Studio Data Architect

With round-trip database support, data architects using ER/Studio Data Architect have the power to easily reverse-engineer, compare and merge, and visually document data assets residing in diverse locations from data centers to mobile platforms. Enterprise data can be more effectively leveraged as a corporate asset, while compliance is supported for business standards and mandatory regulations -- essential factors in an organizational data governance program. A range of data sources are supported ranging from those residing on the cloud to data sources residing on mobile phones. A variety of database platforms, including traditional RDBMS and big data technologies such as MongoDB and Hadoop Hive, can be imported and integrated into shared models and metadata definitions.

"ER/Studio has been an invaluable tool for putting standards in place for designing and maintaining databases."
– Beaumont Hospital

Establish Your Data Architecture

The Compare and Merge Utility ER/Studio Data Architect provides an easy-to-use visual interface to document, understand, and publish information about existing databases so they can be better harnessed to support business objectives. Powerful reverse engineering capabilities allows a data modeler to compare and consolidate common data structures without creating unnecessary duplication.

The ER/Studio Data Architect Professional edition also includes the model repository for version control. This provides a secure and scalable environment for model and object version management. With a 64-bit memory model, larger data models can be processed with improved performance on key operations such as compare and merge.

In addition, with tighter integration with mobile databases, ER/Studio Data Architect allows data modelers to reverse engineer databases used in mobile applications to document and optimize their performance. The Developer edition is specifically designed to work with our RAD Studio Architect edition.

ER/Studio Data Architect helps data architects define and reuse common data elements and modeling components across modeling practices. By enforcing standards, and analyzing data elements, corporations can better understand and utilize their data and reduce redundancy.

ER/Studio provides dimensional modeling capabilities ER/Studio Data Architect brings clarity to models and to complex business rule enforcement. The multilevel design layers allow for the accurate visualization of data, which promotes communication between business and technical users.

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.

The Challenge of Fully Leveraging Enterprise Data

Where Used impact analysis

As organizations grow and data proliferates, ad hoc systems for storing, analyzing, and utilizing that data start to appear. You need the ability to import and reverse-engineer content from multiple data sources and integrate the elements into reusable constructs with an enterprise data dictionary. Data Architect now includes the import bridges for common modeling tools, to easily migrate their native formats into ER/Studio.

Data management professionals face three distinct challenges:

  • Reduce duplication and risk associated with multiple data capture and storage environments;
  • Maximize data quality and re-usability across the organization;
  • Clearly and effectively communicate data to all users.

Accurate interpretation and re-use of essential data throughout an organization can enable better decision-making.

ER/Studio Data Architect documents and enhances existing databases, improves data consistency and effectively communicates models across the enterprise. With ER/Studio, you can leverage your enterprise data as an asset, while complying with business standards and mandatory regulations.

Are you using ERwin? Learn how ER/Studio compares! ›

ER/Studio vs ERwin


ER/Studio Data Architect provides built-in facilities to automate routine modeling tasks so data modelers and architects can analyze and optimize database and data warehouse designs faster than ever.

  • Document and enhance existing databases
  • Improve data consistency
  • Effectively communicate models across the enterprise
  • Trace data origins and whereabouts to enhance data integration and accuracy

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