Data modeling tools speed and improve the process of creating and managing a data model, or 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 also open-source data modeling tools, but they generally don't offer the functionality required by most modern enterprises.

ER/Studio allows you to easily implement 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. With Data Architect Professional, you can also integrate model elements into reusable constructs via a built-in enterprise data dictionary.

IDERA’s ER/Studio suite of data modeling and architecture tools enables IT teams to create the foundation of a viable data governance program, fostering collaboration that’s required to define enterprise data resources business-wide. Instituting a strong data governance policy is critical to maintaining airtight data security. Data governance helps organizations identify data that is at risk, locate sensitive data, identify sensitive data users, and ensure safer access.

A data governance framework is a set of rules, processes, and role delegations aimed at ensuring everyone within an organization understands how to use and organize data. ER/Studio makes it simple, easy, and intuitive to implement naming conventions and other guidelines to form the base of a robust data governance framework.

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.

A data model is typically created using two sets of guidelines: the business requirements, and the data at hand. Data models all serve a business purpose, and they should be created and tailored to fit that purpose. A tool like Idera ER/Studio helps streamline the process of identifying the overlap between data and business requirements and building a model that accurately addresses those needs.