Data Asset Design Automation
Utilize rule-based automation
to streamline data asset design tasks With Idera ER/Studio
Rule-based transformation
Simplify and streamline the process of producing physical models from logical models
Intuitive standards management
Automatically enforce and manage standards across data projects with Data Dictionaries
Streamlined change requests
Easily incorporate and reconcile changes from different users
Robust data asset documentation
Support data governance initiatives with the built-in Business Glossary
Simplify and streamline the process of producing physical models from logical models
Idera ER/Studio makes it quicker, easier, and more intuitive to capture business requirements in logical and physical data models, saving time and increasing organizational efficiency. One of the key ways it achieves this is by streamlining the technical design of a data asset from a logical model. ER/Studio allows users to create rules that are customized to their business needs, which can then be applied over and over again to automate tasks that database administrators (DBAs) find themselves performing frequently, saving time and increasing efficiency.
Automatically enforce and manage standards across data projects with Data Dictionaries
A Data Dictionary allows database administrators (DBAs) and other key stakeholders to build out a list of their most-used data elements, which can then be automatically used in logical and physical data models. This achieves two main things: it saves DBAs time by removing the need to repeatedly define the same data elements, and it ensures that standards are maintained across the enterprise. Standards management is critical to maintaining a clean and usable data asset — and shouldn’t be left to chance. ER/Studio’s Naming Standards Utility automatically applies given naming standards to models or objects within the model, ensuring that everyone in the organization is speaking the same language when it comes to data asset design.
Easily incorporate and reconcile changes from different users
ER/Studio’s Compare and Merge utility eliminates much of the legwork of data normalization, as it allows users to automatically reconcile differences between a model and a database or between models in the same file. For example, if one user makes a change to a table in a model while another alters a table in the related database, the Compare and Merge utility will automatically propagate both changes across the whole data design cycle to ensure information remains consistent organization-wide.
Support data governance initiatives with the built-in Business Glossary
With the built-in Business Glossary, Idera ER/Studio makes it far easier for data architects to support data governance requests and ensure projects comply with organizational and industry policies. The Business Glossary allows DBAs to automatically document data assets against set data governance standards as they move through the data design cycle, ensuring a high quality of data is maintained throughout the data asset design process. ER/Studio is the leading data asset modeling tool on the market with this functionality.
Frequently-Asked Questions
Database design is the process of creating logical and physical data models to govern a database system. The goal of database design is to ensure the accuracy and comprehensiveness of the information contained in a data asset while also avoiding redundancy and other inefficiencies. A well-designed database allows organizations to easily find, access, and retrieve information whenever needed, eliminating waste and saving time.
In short, a physical data model is the database representation of a logical data model. A logical data model is a communication tool used to “translate” between business needs and database design, using concepts and terms that business analysts without technical backgrounds can understand. A physical data model is the expression of the logical data model in the data asset design. A physical data model includes tables, columns, keys, validation rules, domains, and access constraints. A logical model uses entities, relationships, and attributes to describe what the physical data model should do.
Data normalization is essentially the process of organizing and “cleaning up” data in order to ensure users can properly utilize a data asset for queries and analysis. Normalization involves eliminating redundancies, logically grouping data to make it easier to find related data assets, and resolving conflicting data. Data normalization is critical to ensuring a data asset can be used easily and successfully.
Automate, streamline, and improve data asset design with a robust data modeling toolbox.
Idera ER/Studio
- Document Data Assets
- Collaborate Across the Model Repository
- Establish a Data Governance Foundation
