erwin Data Modeler by Quest is a data modeling tool used to find, visualize, design, deploy and standardize high-quality enterprise data assets. It can discover and document any data from anywhere for consistency, clarity and artifact reuse across large-scale data integration, master data management, metadata management, Big Data, business intelligence and analytics initiatives, accomplishing this whil esupporting data governance and intelligence efforts.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Senior Oracle Database Administrator in Information Technology at CGI (10,001+ employees employees)
Pros
Reverse Engineering: I love the way we can import an SQL file containing schema meta data and generate ER diagram out of it. This is specifically useful if you are implementing erwin Data Modeler for an existing database.
Forward Engineering: We use this feature very frequently. Where we do database changes in our physical and logical data models and then generate deployment scripts for the changes made.
Physical vs Logical Models: I like to have my database model split into physical and logical models and at the same time still linked to each other. Any changes you make to logical model or physical model shows up in the other.
Cons
For large models, it gets tedious to print the diagram in a single pdf. I have to often make adjustment and if i use the fit model feature, it kind of changes the alignment of entities in my ER diagram. Erwin may let us make pdf of the model as is.
I have used reverse engineering using for Oracle schemas. It will be very good if it supports reverse engineering for more vendors, so i can use erwin data modeler for database conversion activities too.
Return on Investment
erwin Data Modeler had been a great tool for our database development and application DBA teams. The thorough data modeling and release control helps us to back trace any issues which are pointed to us at a later stage in the development cycle.
Initially, some of the team members saw it as an extra effort to maintain data models while they can simply create scripts without models. But overtime, people have realized how it avoids problems and discrepancies over time.
Alternatives Considered
Toad Data Point
Other Software Used
Google Authenticator, Oracle Cloud Infrastructure Database, Cisco Webex Teams (formerly Cisco Spark)
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Verified User
Employee in Information Technology (10,001+ employees employees)
Pros
Easy to reverse engineer existing databases to bring them into the model or account for drift.
Intuitive interface for developers just starting out with the tool.
Large number of options on how to display a data model visually, which is critical when dealing with very large models.
Cons
Cost is the single largest barrier to entry with this tool.
Would like to see a greater variety of export options available for use outside of the tool, for example as a vector graphic.
Support has been uneven at times.
Return on Investment
Reduced rework from when models were maintained individually.
Reduced the amount of time to generate and compare models during development.
Massively reduced the amount of time to reverse engineer 3rd party data models for analysis.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Verified User
Director in Professional Services (10,001+ employees employees)
Pros
Generation/management of DDL.
Enforces standard naming conventions.
Builds logical and physical data models.
Cons
User interface
Many options available to learn.
Return on Investment
Standardization of Data Models
Generate Data Dictionaries
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