erwin Data Modeler by Quest Reviews

We are using it for a very specific use case, and it works pretty well for us. We do all of our database modeling based on this tool, and it is a repository of all data models in our business intelligence ecosystem. The logical representation of our metadata and anything that is created in a database, such as tables, is in it. 

It is an on-prem workgroup. We have a workgroup server that hosts our model.

We utilize it for its cross-database capability and logical representation of the data model. We have recently started to use its collaboration features, and we also use it to define all our relationship constraints and referential integrity within our data model. So, a lot goes out of it.

It has standardized our practices. For example, all customer-related entities and attributes have to follow a certain naming convention. It has helped in standardizing the process of creating our data models so that when we go and explore the data, we can combine them in a way in which we are confident of producing the right results. It has made a lot of difference in terms of naming standards, processes around our metadata, and the schema in which we create a database. We have a proper template to put the information through a well-structured data model. It helps users in getting the maximum value of the information that is available in the BI ecosystem. erwin Data Modeler makes it very simple and easy to navigate our very complex data.

Its visual data models are very good and helpful for overcoming data source complexity and enabling understanding and collaboration around maintenance and usage. We have a complex business environment where we have retail and supply chain space for distribution. There are a lot of cases where we use the models for customer promotions and events and loyalty systems. Different data modelers can do their own subject areas, and then they can bring them together in a workgroup workspace. It has allowed us to collaborate and distribute the data modeling work. Previously, it used to be very single-threaded. Now, a lot of different teams can run their own modelers, and then, later on, integrate them, which is very useful. It is also very useful in the database migration process. You can take a logical model and seamlessly transfer it over to the database. That's very useful as well. 

We use its modeling support for Snowflake Cloud. We don't use it in any special way. We use it the way we use an existing on-prem database. It just needs to follow Snowflake conventions, which it does. We have a standard logical model that can then translate to a physical model for any database we choose, and that's where erwin has been very helpful. We can set those naming standards, and it also does logical to physical translation seamlessly. This support for Snowflake is helpful. We have enough help to port our model from DB2 to Snowflake in terms of model creation. It has proven very helpful that way.

It can create table structures across a wide variety of sources, which is very useful for us. It cuts the development time of our database code quite a bit. Otherwise, we would have to rely on Excel sheets. Currently, our average project size is anywhere from 3,000 to 4,000 hours, and out of that, we spend around 5% on data modeling. If we didn't have this tool, it will take almost twice more time for any project.

It allows us to create logical data models. We can represent a database model in business terms, which is very useful for us. 

It supports a wide variety of databases, including the latest ones. We have chosen to go for a cloud-based database, and it supports that, which is very useful. 

It is very useful for maintaining relationships between tables. We can put constraints and foreign key-primary key relationships into the model, and it gets translated into the physical database seamlessly. 

Workgroup is another useful feature to store and share the models with the team for collaboration. 

In terms of improvements, support could have been better in terms of installation, especially of workgroups. We struggled quite a bit to get it up and running. Collaboration could have been better from an installation perspective, but it is trivial as compared to what we use it for. Other than that, I don't have much feedback. It works pretty well, and the fact that we've been using it for more than a decade shows that it is quite solid. 

In terms of new features, it would be great to have a cloud base. We should be able to put it on the cloud for better collaboration and data models sharing.

I have been using this solution for more than a decade.

It is very stable.

It is fairly scalable. We really haven't pushed it to the limit with respect to scalability, but we haven't found any issues.

Currently, we have around 20 users. They are mostly data modelers and data engineers. We have plans to increase its usage as deploy additional systems in our business unit. So, there are plans to scale up, but not in the immediate future.

I have interacted with their technical support. I would rate them an eight out of 10.

I have been in this company only for two years, but from the licensing, I know it has been more than 10 years. I am not aware of any other tool being used previously.

There wasn't a lot of stuff. When things didn't work, we had to go and figure out why this isn't working and which ports should we open. There was a lot of back and forth communication with their support, and they were very helpful, but it gets pretty difficult when something that could be done in one to two hours takes you longer than that. It took us a few weeks to get it right, but once it started working, it was pretty seamless.

There was no implementation strategy. You just download an installable and install it. The problem is that it requires a database, and it requires a particular configuration. All this is documented, but it doesn't work the way it is documented. So, it took time for us to figure out, "Hey, this thing is not working. Why is it not coming up?"

For maintenance, we don't have anyone. For the deployment of the workgroup, it took just one person. My data engineering lead just went and did it all by himself. It is a pretty simple product. It just took us a while to figure it out, especially the collaborative tool. Generally, it is supposed to take half an hour for one person.

We installed it ourselves. We did not use anybody to install it, maybe that's why it took us longer.

I don't have the metrics, but I would say we have seen an ROI. It has brought down the cost of implementation in terms of manpower. It might have saved us thousands of hours. It could also be more than a hundred thousand hours. 

The accuracy and speed of the solution in transforming complex designs into well-aligned data sources make the cost of the tool totally worth it.

There are no costs in addition to the standard licensing fees.

In general, for its purpose or use cases, it is the best tool in the market. It does its part in terms of metadata, but we have other challenges that erwin cannot resolve. We have a large pool of legacy data sources that are not labeled, and erwin really can't help there. I don't see any other tool filling that space unless we go for a catalog, which is a different product space altogether. erwin can process the legacy files, but we're just not using it for that because we don't have the bandwidth.

You need a skilled modeler to start off. It really depends on what kind of organization is implementing it: small scale, mid scale, or big scale, but collaboration really works. It is a very good tool, but proper training would be required to take full advantage of the tool. It helps to do a lot more on the job. You would need a lot of discipline before you start using the product. The standards and governance should be put up front before it can be utilized effectively.

The biggest lesson that I have learned from using this solution is that it cannot resolve governance issues. You need to have proper standards in place before you start using this tool. Bad processes lead to bad outcomes. The tool will help you shepherd those processes, but it doesn't solve them. So, you need to have proper process governance and standards. You need to make the tool enforce those processes and standards. You should have proper controls on the data inside in order to get the best results. Governance and process discipline are pretty important. 

On the database side, I come from organizations where some people follow one standard, and other people follow another set of standards, and if we use the same database and tools, then you get a mess. That's where the process discipline comes in for unified governance, which has got nothing to do with the tool. It has everything to do with how the organization is structured. The tool will help you to control that.

I would rate erwin Data Modeler a nine out of 10. If it can be on the cloud without any installs, that would make it a 10.

We use erwin Data Model to create logical and physical data models.

The solution has been very helpful. The logical and physical data models provide visualization for communication across the business, among the data team, and technical team. Without this solution, communication would be difficult.

The ease and quick ability to create the model is valuable. The fitting model is very intuitive. 

The other cool feature is the reverse engineer feature. If we connect to the database, we can reverse engineer from the database itself of the physical model. That gives us the relationship of the data if not much documentation is available.

So far, we have used it in either a workroom version or a standalone version. It does not have a cloud application.

We have licenses for Mac Linux since a lot of our people have Mac laptops, so erwin should work on their cloud application.

I have been using erwin Data Modeler since 2006. 

It is a stable solution. So far, we have not had many problems. Sometimes it freezes because it is a resource-hungry application, so it uses a lot of memory and a lot of processing power while running. But so far, we have not lost any of our work.

We had a concurrent license where multiple people could it. Typically, this is not a tool that you’ll use for hundreds of people. It’s very scalable for ta limited number of people.

The technical support team is pretty prompt. The tier-one support is pretty prompt. We contacted them a couple of times for a security patch and a few times for transferring the license to a different user. Their support was good.

Positive

I have tried Lucidchart, PCO, and ER Studio.

erwin and ER Studio are very comparable. I personally think both are more or less the same. However, erwin has richer features, and productivity is boosted. Once I have a model in mind, putting that in the tool is very quick, followed by generating the DDL, creating the table, and integrating it with the data explorer. The bulk editor feature is also very useful. 

The initial setup is straightforward for someone who understands the data.

For the workgroup version, you need to set up a database and then connect to the database. After installation, you have to maintain those connections. For someone who is well-converged with a database, it’s simple. If someone has not worked with web databases, they might find it a little complex. The deployment was done within a couple of hours by three to four people.

The deployment was done in-house.

There is either a one-year or three-year license. It is not a pay-as-you-go license like a SaaS solution. It’s more of a traditional licensing. They are a little bit on the pricier side.

However, there are tools that are less pricey, and some of them are open source and free as well.

From a pricing perspective, it is not very competitive in the current market.

I would rate the erwin Data Modeler an eight out of ten.

They have small videos that explain how to use the tool and they are very useful. If you know the principles of data modeling, erwin will be very easy to learn. If you are new to data modeling, then I’d recommend getting a course on data modeling first.

The use cases are for our enterprise data warehouse where we have an enterprise model being maintained and we have about 11 business-capability models being maintained. Examples of business capabilities would be finance, human resources, supply-chain, sales and marketing, and procurement. We maintain business domain models in addition to the enterprise model.

We're on-premise, a virtualized data center. We're running this as client-server, the client being PC-driven and the back-end for the erwin Mart is virtualized Windows Servers.

Collaboration is very important because it's important to have an enterprise-view of data, as opposed to a project-specific view of data. Using the business capability models, we're able to augment those models based on a project-by-project implementation. And each of those implementations goes through a review process before those business capability models are finalized. That adds a lot of value in data consistency and data replication when it comes to the models. We can discover where there is duplication and inconsistency. It also helps with the data descriptions, the metadata, about the purpose of using certain designs and certain descriptions for tables and patterns, for the data elements. It helps enforce the data standards that we've adopted.

Each data modeler has their own way of designing the models, but no modeler is starting from a blank sheet of paper. By reverse-engineering models, and by creating models that are based off of popular packages — for example SAP or JD Edwards or Workday — you're able to construct your own data model and leverage the metadata that comes along with the application models. You are able to integrate the data based on these models.

These modeling tasks deal with applications, and some of the applications are mission-critical and some are not. Most of the applications are not; it's more an analytical/reporting nature that these models represent. The models are key for data discovery of where things are, which makes it more transparent to the user.

The solution's code generation pretty much ensures accurate engineering of data sources. If you're reverse-engineering a data source, it's good to have the script for examination, but it's valuable in that it describes data elements. So you get accurate data types from those. It cuts down on the integration development time. The mapping process of source-to-target is a lot easier once you know what the source model is and what your target mapping is.

The most valuable features are being able to visualize the data in the diagrams and transform those diagrams into physical database deployments. These features help, specifically, to integrate the data. When the source data is accumulated and modeled, the target model is in erwin and it helps resolve the data integration patterns that are required to map the data to accommodate a model.

Also, collaboration around maintenance and usage is associated with data model development and expertise coming from a review process, before the data is actually deployed on a platform. So the data models are reviewed and the data sources are discovered and profiled, allowing them to be mapped to the business capability models.

The modeling product itself is far and above anything else that I've seen on the market. There are certain inconsistencies when it comes to keeping up with other platforms' databases in the reverse-engineering process. It should also support more database platforms.

There should also be improvements to capture erwin models in third-party products, for example, data catalogs and things of that nature, where the vendors have to be more aware of the different releases of product and what they support during that type of interaction. Instead of being three or four releases behind from one product to another, the products should become more aligned with each other. So if you're using an Erwin model in a data catalog, you should be able to scan that model based on the level of the Erwin model. If the old model is a certain release, the capture of that should be at the same release.

I've been using erwin Data Modeler since 2014.

There haven't been too many problems with stability so we're pretty pleased with the stability of it. Once in a while things may go awry but then we open up a request.

We haven't had any issues with scalability. Licensing is very supportive of the scalability because of the type of license we use, which is concurrent. We don't anticipate any issues with scalability: not in terms of the number of users and not in terms of the scalability of some of the models. 

Some of the models are quite large and therefore our data modeling framework helps us because we're able to have multiple models that are loosely coupled and make up our enterprise model. So we're not maintaining one model for all the changes. We're maintaining several models, which makes it a lot easier to distribute the scalability of those models and the number of objects in those models.

Technical support has been pretty good. We've had licensing issues. There have also been some bugs that have been repaired and there have been some issues with installation. But all in all, it's been pretty good.

We did not have a previous solution.

The initial setup was pretty straightforward. 

The only thing that we would like to see improved would be having the product support a silent install. If we were able to deploy the product from a predefined script, as opposed to a native installation, such as on a Windows platform, that would help. We are such a large company that we would prefer to package the erwin installation in one of our custom scripts so we could put it in our application store. It's much along the lines of thinking of an iPhone or an Android application in an application store where you're able to have it scripted for deployment, as opposed to installing it natively.

Our deployment took just a few months. We constantly go through deployments as new people come onboard, especially consultants. Usually, with a consultant engagement using a data modeler, you have to be able to deploy the software to them. Anything that helps them out in that process is good.

Our deployment plan was to test the product in a development environment, and have people trained through either self-service video instruction or through on-the-job-training. We were then able to be productive in a production environment.

ROI is hard to measure. If we did measure it, it would be more of a productivity jump of around 10 percent and would also be seen in data standardization. All of these numbers are intangible. There is more of an intangible benefit than a tangible benefit. It's hard to really put a dollar on some of the data governance processes that erwin supports.

Standardization is very difficult to put a price tag on or to estimate its return on investment. But we do have data standards; we are using standard names and abbreviations and we do have some standards domains and data types. Those things, in themselves, have contributed to consistency, but I don't know how you measure the consistency. When it comes to enterprise-data warehousing, it's a lot easier for end-users to understand the context of data by having these standards in place. That way, the people who use the data know what they're looking at and where it is. If they need to look at how it's designed, then they can get into the product a little deeper and are able to visualize the designs of some of this data.

The accuracy and speed of the solution in transforming complex designs into well-aligned data sources absolutely make the cost of the tool worth it. erwin supports the Agile methodology, which tends to stabilize your data before you start your sprints and before application development runs its course.

We pay on a one-year subscription basis.

The biggest lesson that I've learned in using this solution is to have a data governance process in place that allows you to use erwin more easily, as opposed to it being optional. There are times when people like to do design without erwin, but that design is not architected. It pays to have some sort of model governance or data governance process in place, so models can be inspected and approved and deployed on database platforms.

We use it primarily for first drafts of database scripts, both in a relational database environment and other types of environments. The models represent those physical implementations. The database scripting part is heavily modified after the first draft to include additional features of those database platforms. So we find erwin DM less valuable through that and we find it more valuable creating initial drafts and reverse-engineering databases. It cuts development time for us to some degree, maybe 10 percent, but all in all, there are still a lot of extensions to the scripting language that are not included with the erwin product.

In our company, there are about 130 users, globally. From time to time the number varies. Most of those users are either the data modelers or data architects. There are fewer enterprise data architects. The other users would just be erwin Web Portal users who want to have a little bit of an understanding about what's in a data model and be able to search for things in the data model. For deployment and maintenance of this solution we have about two infrastructure people, in an 8 x 5 support model.

The easiest way of exposing or sharing the model to all the users at the enterprise level is the feature I found to be valuable in the solution.

They should merge all those products because apart from the Mark Server, they have the Web Portal, which requires a separate installation and license. And it's not easy to maintain, but very easy to use. So you need additional resources such as memory, unlike if they merge those Web Portal and Mark Server, which would be a great solution.

I think they should be more open to or ready to be agnostic to any databases, such as MongoDB. Any database available in the market should be ready in their drivers because I don't think they can be ready. So all the popular databases like Oracle, MySQL, Microsoft, and SQL Server, but I haven't seen any connector in Cosmos DB SQL, so it should be in the big data or cloud solution.

I have been using erwin Data Modeler for a year.

It is not a very stable solution. I rate the stability five out of ten.

It is a scalable solution. Around 20 users are using the solution presently. I rate the scalability an eight out of ten.

The technical support team is fine.

Previously, we used SAP PowerDesigner. One of the primary reasons we switched to Data Modeler is that we need to expose our models so that the user can access them very efficiently and time-bound. If I develop a model and if it's a room, I can easily push that model into a web portal. The users can study and use it from there, unlike in the previous SAP PowerDesigner. You need to export an image or picture file or JPEG or PNG; then you have to share on SharePoint and upload it in Confluence of this. That is a very tedious way of sharing the model. The stability of the solution needs improvement.

The initial setup is straightforward. The solution is deployed through the desktop version available for Data Artifacts. There is also a repository, the data node, and a web portal which is the application or web application for data analysis and other users interested in starting the model. I did all the deployment.

The pricing of the solution is cheap. I rate the pricing a five out of ten.

SAP solution is more stable compared to Data Modeler and fits our requirements as an enterprise team.

I rate the overall solution a seven out of ten.

erwin is deployed on individual desktops and the individual users install it or have a help desk person install it for them.

Our primary use case is for during any type of project development or maintenance and application maintenance, we go through a process of modeling our data before it gets put into the database. We interact with the application development teams to determine what their requirements are and build the data models, and then turn them into actual physical database items.

erwin has definitely helped us improve our enforcement of standards and database design best practices. Before we really started using the tool or having a data modeling type of team, application development efforts all had their own database structures. Developers tend to not be too concerned with the data. They just want to make everything work for their application as easy as possible. Having the tool and having a team built around it has really helped us make sure that we're following the best normalization processes, we're not duplicating data, and we have a standard naming scheme that everybody has to follow.

The modeling portion of the tool is the most valuable. There are some notes, naming standards, and other functions that we use as well. There's a whole boatload of functionality in this thing and we use maybe 10% of it. It seems to be pretty common that not all the functionality is fully utilized. But it's got gobs and gobs of stuff that you can implement if you so choose to.

We've definitely expounded on the amount of features we use. They've built in some automated naming standards that have been really helpful for us. That's probably the biggest leap we've used. We've always used the comments and notes features, but the automated naming features have been very helpful.

Its ability to overcome data source complexity and enabling understanding and collaboration around maintenance and usage is extremely helpful because they give a visual to not only developers and database administrators, but the user base themselves. So the typical user isn't going to understand database functionality. Being able to show them a picture of how their data is actually going to look in the database is very helpful for their understanding of what we're trying to do with their data.

erwin's ability to compare and synchronize data sources with data models in terms of accuracy and speed for keeping them in sync is very good. We utilize that service quite a bit. The one drawback is if you have an extremely large complex model, the compare process can take quite a bit of time, more than four hours. 

Its ability to generate database code from a model for a wide array of data sources cuts development time. The fact that you can generate the DDL correctly from the model saves us a bunch of time. I would say it saves us around 40% to 50%. So even though you can generate the DDL, you still have to go in and tweak it a little bit. 

The only real complaint I have is the time it takes to do a database comparison on a large model. If they could speed that up, that would be the only thing I can think of that needs improvement.

We've been using erwin since about 2000. We were using another product before, but it was way too cumbersome, so we switched to erwin.

Stability is excellent. It's been a solid product for years and I don't expect it to change.

It's extremely scalable. Our environment has hundreds of tables. 

We have five data modelers using the tool. That's the team that actually works with the app dev and DBAs to actually come up with the database design. Then we have another five users that act more in a read-only type of mode. They just want to look at the data models, but they don't actually do any of the design work.

Their support was excellent. Typically it has to do with going through the upgrade process. If we have an issue, we'll reach out to them. The other thing we've had to reach out to them about was the time it was taking to do a data comparison on our extremely large model to the actual physical database. They were very helpful and very professional.

We don't typically have problems transitioning between the models. We did last time, but it was actually an error on our end. It wasn't an error on the erwin end.

We were using Cayenne. We switched because it was cumbersome.

The initial setup is typically straightforward. Just follow their instructions and everything goes pretty smoothly.

For the Data Modeler portion itself, on each desktop, the setup took around half an hour, and we have around 10 desktops.

We didn't necessarily have a deployment strategy. We just gave the product to anybody that thought they needed it and let them run with it.

For maintenance, we need one person, but it's definitely not a full-time job. It's just adding and subtracting users and going through the upgrade process when we do that. As far as installation, everybody basically installs it themselves. We don't require a full-time person for that either.

We have a team around it, so if we add our data modeling team up, we use it about six hours a day per person. That would be about 18 hours a day for those guys. The read-only users rarely use it, so they're pretty insignificant. 

We probably only use 10% to 20% of the functionality and I don't see us expanding on that a whole lot. There's a lot of neat little things in there, but we don't have time to implement them all. There's some overhead that goes with those functions that we choose not to undertake.

Since we got a new guy on our team, he's gotten into some of those functions and has been able to utilize some of that stuff some more. We're actually probably closer to 30% or 40% of the functions at this point. We're not thinking about expanding because of the overhead. 

I don't remember what our costs are. I know they just recently switched from a per seat type of licensing to a concurrent user type of licensing agreement, which is neither here nor there. I don't think it has increased or decreased the cost at all, but it's not obtrusive or invasive as far as the cost goes. It's fairly affordable.

There are also internal costs if you have hosted on-prem because you have to have a server and database to stand it up on.

We didn't evaluate another solution because I had used erwin at another location and was extremely familiar with it. And I had also used Visio and some more manual-type methods like Visio. At the point that we decided to switch over, I was confident that erwin was the best solution out there.

erwin is by far the best tool I've ever used. 

My advice to somebody considering this solution is to go for it. It's easy. The functionality is fantastic. It's easy to pick up. It does basically everything you could want it to do.

The automation of reusable design rules and standards has helped us immensely once we implemented it because having the automated naming standards and things like that, we don't have to go in and think about it. We don't have to go in and physically type it. Between generating the DDL and getting it into physical implementation was saving us 40% to 50% of time. It's because of those automated features that that's happening as opposed to having to sit there and type out the DDL from scratch, it saves a ton of time.

It produces a time savings of about 40%.

The accuracy and the speed of this solution in transforming complex designs into well-aligned data sources absolutely make the cost of the tool worth it.

My advice would be to let things evolve over time. Start with the basics first. Just get into the ERD functions first and then start implementing some of the automated naming standards and things like that as you go. Otherwise, if you try to dive into the whole thing, you're just going to get overwhelmed because the product is so deep as far as features go. It's extremely intuitive. As far as the basics go, as far as getting your ERDs established, it's probably the easiest tool I've ever used. If you understand the basics of database design, it's extremely natural. If you have no clue about database design, then your learning curve is going to be large no matter what tool you pick. But erwin definitely cuts that learning curve down just because of its intuitiveness.

Once you start diving into the automated feature sets like naming standards and things like that, the learning curve there is a little steeper, but it's still not too bad. For a brand new person, if you try to delve into the automated stuff and all the additional functionality, you're just going to get overwhelmed and feel that there is too much overhead. But you don't need to implement all those features right off the bat.

I would rate erwin a ten out of ten.

We use the erwin Data Modeler tool to document conceptual, logical, and physical data design. Business data models capture the understanding of the data from a business perspective, which can then drive physical design to ensure data is represented and used correctly.

The automated generation of the DDL ensures that the data store looks exactly as the data design. It also ensures that the standards that are governed are followed and implemented successfully.

We use the diagrams and data dictionary capabilities to help users understand the data environments, as well as how the data relates to each other. We'll use the naming standard master file to govern and ensure that we have consistent naming and abbreviations across and within data stores. We use the forward engineering templates to standardize and govern the generation of the data definition language that is used to actually make the changes to the data stores. We also use the Compare capability to ensure that we have up to date production data models. And we are looking forward to the integration of the Data Modeler metadata with the data intelligence suite in R2.

The visual data models for helping to overcome data source complexity and enabling understanding and collaboration around maintenance and usage are excellent. A picture speaks 1,000 words. Seeing a picture that shows you how the data relates to each other helps you better understand what the data is and how to use it. Pairing that information with a dictionary, which has the definitions of the tables, columns, the entities, and attributes, ensures that the users understand what the data is so that they can use it best and most successfully.

Its ability to compare and synchronize data sources with data models in terms of accuracy and speed for keeping them in sync is excellent. 

We don't typically use the configurable workspace and modeling canvas because while the platform allows for the flexibility to dynamically include multiple colors and multiple themes, feedback from business users is that the multiple colors and themes can become overwhelming. When you do that, you need to include a key so that people understand what the colors mean.

Its ability to generate database code from a model for a wide array of data sources cuts our development time. By how much depends on the number of changes that are required within the data store. It is certainly better to automate the forward engineering of the DDL creation, rather than having someone manually type it all out and then possibly make a human error with spelling irregularities.

Its code generation ensures accurate engineering of data sources. It decreases development time because it's automated.

I would like to see the reporting capabilities be more dynamic and more inclusive of information. The API is very sparsely understood by people across the user community.

I would also like to see a greater amount of integration with the erwin Data Intelligence Suite and the erwin Web Portal for the diagram delivery. That would be beneficial to all.

I have been using erwin for twenty years. 

It's very stable, especially having been available for use for so many years.

It is scaling well to include the new data structures, rather than being stagnant and only continuing to support the older DBMS types.

We have over 100 Data Modelers in my company and the users of the metadata go into the 1,000s.

We have an administrator who is responsible for the software upgrades, we have a governance community in the Center of Excellence, and we have the actual Data Modelers themselves who provide the delivery of the physical data models. We have data architects who create business, conceptual, and logical data models. And then, of course, we have our developers who use the data model information to understand the code that they are writing. We also have the business users who use the diagrams and the data dictionaries to understand the data so that they use it correctly.

Data Modeler is being used very extensively. We are considered power users within the community of users.

As new applications are developed, we may or may not need new licenses for erwin Data Modeler.

I have used SILVERRUN, which is a very old tool and actually has Sunset. I have also used SAP Sybase PowerDesigner. The primary reason for using PowerDesigner over erwin Data Modeler for that decision was that we were able to program the PL/SQL right into Sybase PowerDesigner. At the time, it had the capability to order the run of the PL/SQL. So the Sybase PowerDesigner would not make the changes to the database via the DDL, but it also generated the PL/SQL code that moved the data from source to target. That's a capability that erwin Data Modeler has never had. I don't know if it is on the roadmap for inclusion in the future, but I also do not see it as a requirement for erwin Data Modeler going forward because there are many ETL tools out there readily available.

I've also used IDERA. The interesting feature about IDERA that differentiates it from erwin Data Modeler is that the model repository actually separates the logical data models from the physical data models. Whereas erwin is basically the flip of a switch. It's not a true logical model, it's a logical representation of the physical data model.

I think the other thing that sets erwin Data Modeler apart is the model Mart repository, which protects a company's intellectual property within the data models and makes them available across the company so that the information is shared with anyone who has an erwin Data Modeler license. That was not available in SILVERRUN. It was also not available when I used PowerDesigner at the time. It was about 15 years ago for PowerDesigner. It is available for IDERA.

I find the setup straightforward. It is very easy to install. It took minutes.

We have seen ROI.

The reusability of some of the information within erwin Data Modeler, coupled with the capability to govern the information such as the data domains, the naming standard master file, degeneration of the DDL, every piece of automation ensures that there is consistency across and within data stores, and reduces the time to deliver the information because of the automation and governance built into the tool.

Whether or not the accuracy and speed of the solution and transforming complex designs into well-aligned data sources make the cost of the tool worth it would be a judgment call. I do think it is worth it. But of course, in this day and age where people are offshoring all of their work trying to save money, makes one consider the cost of any investment.

I think that the pricing is reasonable. It has called Concurrent licensing, where you can have a number of people share an erwin license. I think that that pricing is a little bit high, but that is a personal opinion.

The biggest lesson that I've learned is actually with a lack of data modeling. We have teams who have complained that data modeling takes too long. They would rather have developers manually code the DDL, which creates a lot of mistakes, increases the backlog, and increases not only the time to delivery but the cost to delivery. There is a lack of understanding of the agile methodology around data modeling and the incorporation of the emergent design happening in the scrum teams with the intentional design of the data architect creating a data model. Given an opportunity to follow the correct path and perform data modeling, we have seen a significant return on investment with decreases in delivery time and decreases in project cost.

I would rate erwin Data Modeler a ten out of ten. 

We use the solution for data modeling.

We believe that the solution would help provide some structure to our data modeling and data design practices.

The product allows us to reuse entities and attributes. Whether we're working on a conceptual or logical model, once we have defined them, we can reuse them rather than defining them all over again. It's a clever feature and helps with our work.

We can only get licenses through partners. We cannot purchase directly from Quest. The partners end up charging a big margin on top of the actual price even though they are not providing any service. It was a letdown.

I have been using the solution for four months.

I rate the tool’s stability an eight out of ten. The tool has crashed a couple of times. The stability must be improved.

I am the only person using the tool in my organization. We plan to increase the usage, but it is currently not being used much.

The support personnel are a bit slow in responding. The vendor talks about providing 24/7 support, but it could take 24 to 36 hours to get a response. The communication is just via email. It slows down the whole troubleshooting process.

Neutral

The initial setup was easy. I rate the ease of setup a ten out of ten. It took me five minutes to deploy the product. To deploy it, I downloaded the software, ran the executable, and it installed itself. I did the deployment myself.

The solution is expensive. I rate the pricing a nine out of ten. The price is not fixed. The product does not have a clear pricing model.

We evaluated ER/Studio but did not like its pricing structure. They have different versions which require multiple licenses for the applications we use. It was not easy to use. We preferred the pricing model of erwin Data Modeler.

The amount of data the tool works with is minimal, so scalability is irrelevant to the tool. It just uses metadata. People looking to use the solution must compare it with other tools like ER/Studio. ER/Studio and erwin Data Modeler are quite similar in the functionality they offer. It all comes down to what works for us in terms of pricing. Overall, I rate the solution an eight out of ten.

In one of the companies, we used it as an information tool. We created a logical model so that the business would know what was in the offices down to the warehouse. The current use case is also the same. We have some places for information, so we can do a logical data model for them, but, usually, it would go towards building an actual database, which also involves reverse engineering of an existing one because people don't know what's in there.

It is currently on-prem, but we still have a separate server.

We want to bring different erwin components together and tell a business user story. So, having all of it on one platform to be able to tell one story makes it not as fragmented as components have been in the past. 

In my previous company, when we had 1,000 tables, 6,000 columns, and 14 subject areas, trying to explain to people in the organization was difficult. Without the tool, it would have been impossible. With the tool, it was a lot easier because you could show a steward how this is his or her domain. For each steward, you could say, "Well, this is your domain over here." Once they had that, they could understand what you were talking about. So, it improved communication. We had a point where two stewards were looking at the models, and one of them said, "I think that one that you've got over there is actually mine." The other one said, "I think you're right." So, we actually moved an entity from one subject area to another because now they had the ability to see what was in their subject area. They could go and see what wasn't theirs and should be someone else's. If we didn't have the tool, we wouldn't have that visibility and wouldn't have been able to recognize that sort of situation. 

Its ability to generate database code from a model for a wide array of data sources cuts development time. You don't have to re-key things. You put in the information at one spot, and it flows out from there. There are so many parameters you can put on the physical side. You can put in your indexes, and you can put in expected size changes. You can store all sorts of information within the model itself. It is a really good repository of all that sort of information, and then you just push a button, and it generates the other end. It works really well. In terms of time-saving, if you had to write it all out by hand, it would take weeks. It would probably take three or four times longer without the tool.

It certainly improves accuracy for the generation of target databases because you're only putting information in one spot. You don't have to retype it. For example, I saw the word conceptual model misspelled today. So, if you have to re-key something, no matter how careful you are, you're going to misspell things, which would cause problems down the track, whereas if you make a mistake in DM, there is only one place you have to go and fix it, and then, you would regenerate the downstream stuff. This means that you don't have to touch anything physical. You generate it, and then you can use it.

Being able to point it to a database and then pull the metadata is a valuable feature. Another valuable feature is being able to rearrange the model so that we can display it to users. We are able to divide the information into subject areas, and we can divide the data landscape into smaller chunks, which makes it easier to understand. If you had 14 subject areas, 1,000 entities, and 6,000 columns, you can't quite understand it all at once. So, being able to have the same underlying model but only display portions of it at a time is extremely useful.

I am currently trying to compare and synchronize data sources with data models, and it is pretty good. It shows you all the differences between the two systems. After that, it is a matter of what you want to do with them. It is certainly helpful for bringing models in and being able to compare. At the moment, I'm comparing something that's in a database with something that was in the DDL statement. So, these are two different sets of sources, and I can bring different sources together and compare them in the one, which is really helpful.

I still use Visio for conceptual modeling, and that's mainly because it is easier to change things, and you can relax some of the rules. DM's eventual target is a database, which means you actually have to dot all the Is and cross all the Ts, but in a conceptual model, you don't often know what you're working with. So, that's probably a constraint with erwin.

They have made it a lot easier, and they've done a lot, but there is probably still room for improvement in terms of the ease of presentation back to the business. I'm comparing it with something like Visio where you can change colors on a box, change the text color and that sort of stuff, and change the lines. Such things are a whole lot easier in Visio, but once you get a theme organized in erwin, you can apply that theme to all of the objects. So, it becomes easier, but you do have to set up that theme. I think they've got three to four initial themes. There is a default theme, and then there are two or three others that you can pick from. So, having more color themes would help. In Visio, you have a series of themes where someone who knows about color has actually matched the colors to each other. So, if you use the colors in the theme, they will complement each other. So, erwin should provide a couple more themes.

They could perhaps think of having an entry-level product that is priced a bit lower. For extra features, the users can pay more.

I have been using it at least since 2003. I have used it at multiple organizations.

It has always been really stable in the different organizations that I've used it in. It has always been a pretty good product.

It works fine with the number of people who have been using the product. We're talking about 10 to 12 people, not thousands of people. I haven't ever been in an organization where thousands of people even needed to get to the product. Probably the biggest drawback in scalability is the cost per seat rather than the actual product. The product works fine.

Our current organization has probably about 5 to 10 people using it. We're a consultancy, so we're using it in various roles. So, a lot of it is to do with understanding. As consultants, we try to understand what a client has in the organization and what sort of data they have to make sure there is actually data in the system that can answer their business questions. So, that's the sort of thing we use it for. We can turn around and give them designs. We can show what it is, and then we can turn around and make it what it would be. It is used by analysts and developers. They are not developing software. They are probably developing the database, but then, people would develop software.

I've used it on all the projects I've been on so far. I've been with this company for a short time, and it has come into play for pretty much all of the projects that I've been on. We want to use it more extensively. We want to use the erwin suite. We've got the modeler, but we also want to use their BI tool. We would like to evolve and come up with a story that links all of them together.

We have only just got the BI suite installed. We're starting to play around with it and see what we can do with it. We're doing some training on it at the moment. In a previous company also, somebody from erwin came to show it to us, and it was reasonably new at that point. That was last year. It is a reasonably new product. So, getting them to talk to each other has also been fairly new. erwin has only done it in the last couple of years. 

I haven't had dealings with them, but the dealings I've had with erwin as a company have always been really good. So, I would rate them a nine or 10 out of 10.

I use Visio on the conceptual side. We've got Informatica, and I think it has got a modeling component in there. We try to get a range of products because we're doing consulting in various organizations, and they have got various tools. Usually, it depends on what a client has already installed. Sometimes, it also depends on their budget. Something like Informatica is usually at the top right end corner of the Gartner Quadrant, but it could also be overkill for smaller organizations because the benefit may not be there. So, a lot of time, it is horses for courses. You have to sort of tailor any solution to meet a client's needs.

I haven't ever really installed erwin. One of the other guys has done that. Most of the places had it installed already. Usually, the complexity depends on how the organization does its software deployment. So, you have to go and request the software and then somebody has to give you the package. Once you get the package, it is pretty straightforward. It is usually less of a problem on erwin's side and more of an issue with how an organization deploys any erwin software, but once you deploy it, it works fine.

Some places that I've worked with were very strict about doing testing on COTS products to make sure that there are no viruses on it and also to make sure that it plays nicely with the rest of the system. So, those sorts of organizations may take longer in terms of testing. You put it on a test machine first and make sure it is not going to kill anything. They might have to repackage some stuff before they put it out to the network. To deploy a vanilla thing, I would think that it would only take a couple of hours.

In terms of maintenance, at the moment, I think we've got one person. The main thing is deploying new versions. You've got a server stood up, and you have to put the software out there. I don't know if there is anything else beyond that.

We haven't done an ROI for the current version. When you look at the total cost of creating or understanding what you've currently got through reverse engineering, and you look at the total cost of creating new products and new databases and maintaining them over time, and then you put that into the return on investment model, it is well worth it.

The accuracy and speed of the solution in transforming complex designs into well-aligned data sources make the cost of the tool worth it. If you didn't have the tool and a single developer or a single modeler was trying to do the same thing, the speed would be three or four times slower. If you multiply that by the cost of that person and then you also consider the cost of the other people who are waiting for that person to create a database design, it multiplies out. So, it is well worth it.

It has increased in price a fair amount over the years. It has always been expensive because it is a comprehensive product, and presumably, they have to do a tremendous amount of testing to make sure that everything works. It has always been dear because usually, a very specific target audience of data architects has the need for modelers, and not everyone in the organization would need to get a copy of it. Only people who are actually working in the database space need it. So, it has always been a very specialized piece of software, and it has been priced accordingly.

I don't specifically know what we're paying now. About three years ago, in another organization, I have this memory of 6,000 AUD a seat or something like that, but I am not sure. In the mid-2000s, it was something like 1,200 AUD a seat. I get the impression that there was a price jump when it was spun off from CA as a separate company, which is understandable, but it could sometimes be a barrier in some organizations picking it up.

I haven't talked to erwin people yet, but I'm going to suggest to them that they could perhaps think of having an entry-level product that is priced a bit lower, and then, you can buy the extra suite. That's what Microsoft does. They package a few things so that you have something, but if you want this extra stuff that has enterprise features, such as they talk to each other and have great bits and pieces, you have to pay more. I don't think there are any additional costs. It is per product, and there are different license levels. 

Oracle Data Modeler, which is free, is one of the competitors that erwin has. You can't argue with the price point on that one, but erwin is much more comprehensive and easier to use. It is easier to display information and models to business people than something like Oracle Data Modeler, which does the job, but erwin does it a lot better. So, my advice would be that if you can afford it, get it.

Its visual data models have certainly improved over time in terms of overcoming data source complexity and enabling understanding and collaboration around maintenance and usage. It was originally designed as a tool to build databases with, and it retains a lot of that. It still looks like that in a lot of cases, but it has also been made more business-friendly with a sort of new front end. So, it used to be all or nothing where when you wanted to show somebody just the entity names or just the entity descriptions, you had to switch all of the entities on your diagram just to show names. Now, you can show some of them. You can shrink down some of them, and you can keep some of them expanded. So, it has become a more useful information-sharing tool over time. It is extremely helpful.

In my previous company, it was the enterprise data model, and you could paper a room with it if you printed the information out. To present that information to people, we had to chunk it down into subject areas. We had to present smaller amounts of information. Because it was linked to the underlying system, we could reuse the information that we had in a model in other models. The biggest lesson was to chunk the information down and present it in a digestible form rather than trying to show the entire thing because otherwise, people would run away screaming.

One of the places didn't have a modeling tool in it, and they were trying to do the documentation using Confluence. It was just a nightmare trying to keep it maintained with different developers using different tables and then needing to throw something into one and adding something into another one. It was just a nightmare. If they had one tool where they could put it all in one place, it would have been so much easier than the mess they had.

I would rate erwin Data Modeler a nine out of 10.