erwin Data Modeler by Quest Reviews

I am responsible for both a combination of documenting our existing data models and using erwin Data Modeler as a primary visual design tool to design and document data models that we implement for our production services.

My primary role is to document our databases using erwin to work with people and ensure that there is logically referential integrity from the perspective of the data models. I also generate the data definition language (DDL) changes necessary to maintain our data models and databases up to our client requirements in terms of their data, analytics, and whatever data manipulation that they want to do. I use erwin a lot.

It is either installed locally or accessed through a server, depending on where I have been. I have had either a single application license or pooled license that I would acquire when I open up erwin from a server.

We get data from many different sources where I work. We have many clients. The data is all conceptually related. There are primary subject area domains common across most of our clients. However, the physical sources of the data, or how the data is defined and organized, often vary significantly from client to client. Therefore, data modeling tools like erwin provide us with the ability to create a visual construct from a subject area perspective of the data. We then use that as a source to normalize the data conceptually and standardized concepts that are documented or defined differently across our sources. Once we get the data, we can then treat the data that has been managed somewhat disparately from a common conceptual framework, which is quite important.

At the moment, for what I'm doing, the interface to the physical database is really critical. erwin generally is good for databases. It is comfortable in generating a variety of versions of data models into DDL formats. That works fine.

What has been useful, I have been able to reverse engineer our existing data models to document explicitly referential integrity relationships, primary/foreign keys in the model, and create ERDs that are subject area-based which our clients can use when working with our databases. The reality is that our databases are not explicitly documented in the DDL with primary/foreign key relationships. You can't look at the DDL and explicitly understand the primary/foreign key relationships that exist between our tables, so the referential integrity is not easily understood. erwin has allowed me to explicitly document that and create ERDs. This has made it easier for our clients to consume our databases for their own purposes.

Its visualization is the most valuable feature. The ability to make global changes throughout the data model. Data models are reasonably large: They are hundreds, and in some cases thousands, of tables and attributes. With any data model, there are many attributes that are common from a naming perspective and a data type perspective. It is possible with erwin to make global changes across all of the tables, columns, or attributes, whether you are doing it logically or physically. Also, we use it to set naming standards, then attempt to enforce naming standards and changes in naming from between the logical version of the data models and the physical versions of the data models, which is very advantageous. It also provides the ability to document primary/foreign key relationships and standardize them along with being able to review conceptually the data model names and data types, then visualize that across fairly large data models.

The solution’s visual data models for helping to overcome data source complexity and enabling understanding and collaboration around maintenance and usage is very important because you can create or define document subject areas within enterprise data models. You can create smaller subsets to be able to document those visually, assess the integrity, and review the integrity of the data models with the primary clients or the users of the data. It can also be used to establish communications that are logically and conceptually correct from a business expert perspective along with maintaining the physical and logical integrity of the data from a data management perspective. 

We are not using erwin's ability to compare and synchronize data sources with data models in terms of accuracy and speed for keeping them in sync to the fullest extent. Part of it is related to the sources of the data and databases that we are now working with and the ability of erwin to interface with those database platforms. There are some issues right now. Historically, erwin worked relatively well with major relational databases, like Oracle, SQL Server, Informix, and Sybase. Now, we are migrating our platforms to the big data platforms: Hadoop, Hive, and HBase. It is only the more recent versions of erwin that have the ability to interface successfully with the big data platforms. One of the issues that we have right now is that we haven't been able to upgrade the version that we currently have of erwin, which doesn't do a very good job of interfacing with our Hive and Hadoop environments. I believe the 2020 version is more successful, but I haven't been able to test that. 

Much of what I do is documenting what we have. I am trying to document our primary data sources and databases in erwin so we have a common platform where we can visually discuss and make changes to the database. In the past couple of years, erwin has kind of supported importing or reverse engineering data models from Hive into erwin, but not necessarily exporting data models or forward generating the erwin-documented data models into Hive or Hadoop (based on my experience). I think the newest versions are better adapted to do that. It is an area of concern and a bit of frustration on my part at this time. I wish I had the latest version of erwin, either the 2020 R1 or R2 version, to see if I could be more successful in importing and exporting data models between erwin and Hive.

erwin generally fails to successfully reverse engineer our Oracle Databases into erwin data models. The way that they are engineered on our side, the syntax is correct from an Oracle perspective, but it seems to be very difficult for erwin to interpret. What I end up doing is using Oracle Data Modeler to reverse engineer into the Oracle data model, then forward engineer the DDL into an Oracle syntax, and importing that DDL into erwin in order to successfully bring in most of the information from our physical data models. That is a bit of a challenge. 

There are other characteristics of erwin, as far as interfacing directly with the databases, that we don't do. Historically, while erwin has existed, the problem is the people that I work with and who have done most of the data management and database creation are engineers. Very few of them have any understanding of data modeling tools and don't work conceptually from that perspective. They know how to write DDL syntax for whether it's SQL Server, Oracle, or Sybase, but they don't have much experience using a data modeling tool like erwin. They don't trust erwin nor would they trust any of its competitors. I trust erwin a lot more than our engineers do. The most that they trust the solution to do is to document and be able to see characteristics of the database, which are useful in terms of discussing the database from a conceptual perspective and with clients, rather than directly engineering the database via erwin. 

erwin is more of a tool to document what exists, what potentially will exist, and create code that engineers can then harvest and manage/manipulate to their satisfaction. They can then use it to make changes directly to our databases. Currently, when the primary focus is on Hive databases or Hadoop environment, where there is no direct engineering at this point between erwin and those databases, any direct or indirect engineering at the moment is still with our Oracle Database.

I have been using the solution on and off for 20 to 30 years.

It is pretty stable. Personally, I haven't run into any real glitches or problems with the output, the ability to import data when it does work correctly, the export/creation of DDL, or generation of reports.

We are trying to upgrade. This has been going on now for several months. We're trying to upgrade to the 2020 version. Originally, it was 2020 R1, but I think at this point people are talking about the 2020 R2 version. Now, I'm not part of our direct communications with erwin in regards to Data Modeler, but there are some issues that erwin is currently working on that are issues for my company. This have prevented us from upgrading immediately to the 2020 version.

This gets down to how you do your data modeling. If you do your data modeling in a conceptually correct manner, scaling isn't an issue. If you don't do your data modeling very well, then you are creating unnecessary complexities. Things can get a bit awkward. This isn't an erwin issue, but more a consequence of who is using the product.

In the area that I'm working right now, I'm the only user. Within the company, there are other people and areas using the solution probably far more intimately in regards to their databases. I really don't know the number of licenses out there.

The problem is that our issues are related to interfacing erwin Data Modeler with the Hadoop Hive environments. The issues have always been either what I was trying to do was not fully supported by our version of erwin Data Modeler. People have certainly tried to help, but there's only so much that they could tell me. So, it's been difficult. I am hoping that I can get back to people with some better answers once the newest version of erwin is available to us.

The people who were previously responsible for the database development were very good engineers who knew how to write SQL. They could program anything themselves that they wanted to program. However, I really don't think that they really understood data modeling as such. They just wrote the code. Our code and models are still developing and not necessarily conformed to good data modeling practices. 

In the past, I was involved in the initial setup. In traditional environments, it sets up pretty easily. In my current environment, where I'm trying to get it as intimately integrated with our big data platforms as possible, I'm finding it quite frustrating. However, I'm using an older version and think that is probably a significant part of the problem.

In other environments where I've worked, the solution’s ability to generate database code from a model for a wide array of data sources cuts development time. In this environment, erwin is not very tightly integrated into the development cycle. It is used more for documentation purposes at this point and for creating a nascent code which down the road gets potentially implemented. While it's not used that way at my current company, I think it would be better if it were, but there is a culture here that probably will prevent that from ever occurring.

An issue right now would be that erwin doesn't have a freely available browser (that I am aware of) for people who are not data modelers or data engineers that a consumer could use to look at the data models and play with it. This would not be to make any changes, but just to visually look at what exists. There are other products out there which do have end user browsers available and allow them to access data models via the data modeling tool.

There is another tool now that people are using. It is not really a data modeling tool. It is more of a data model visualization tool, and that's SchemaSpy. We don't do data modeling with that. You get a visualization of the existing physical database. But that's where the engineers live, and that's what they think is great. This is a cultural, conceptual, understanding issue due to a lack of understanding and appreciation of what good data modeling tools do that I can't see changing based on the current corporate organization. 

It is the only meaningful way to do any data modeling. It is impossible to conceptualize and document complex data environments and the integration between different data subject areas. You can write all the code or DDL you want, but it's absolutely impossible to maintain any sort of conceptual or logical integrity across a large complex enterprise environment without using a tool like erwin. 

You want to look at what you are trying to accomplish with erwin before implementing it.

• Does the product have the ability to support or accomplish that?
• Based on the technologies that you have decided you want to use to manage your data, how intimately does it integrate with those technologies? 

From my perspective of using the traditional relational databases, I think erwin probably works pretty well. 

For the newer database technologies, such as the Hadoop environment databases, it's not clear to me how successful erwin is. However, I'm not talking from the perspective of somebody who has been aggressively using the latest version. I don't have access to it, so I'm afraid my concerns or issues may not be valid at this point. I will find out when we finally implement the latest erwin version.

I would give the solution a seven or eight (out of 10).

We have a couple of really important use cases for erwin. One of them is that we automate the pull of metadata from the repository itself, so that we have all the model metadata that we can then put into a centralized hub that we can access with other applications. Another reason we pull all the metadata out of the model is to run it through our model validation application, which telsl us if this model is healthy or not and if it meets our standards or not.

The other use case that's really important is managing the abbreviations file that erwin uses to convert logical terms into physical terms. The way that you manage it today within erwin is very manual and you'll go from a spreadsheet, make changes, and upload, et cetera-- but we've created an API application where if we take the main standard file and keep it in the database, make the changes in the database, then we have an application that goes out into the Mart file, deletes the glossary, replaces it with the table from the database. It's all automated at the push of a button. It's things that would take us days to make changes in the standard files and do updates in eight different files.

Data warehousing is the best example of how this product can make a huge difference because it's an integration of a lot of different source systems. You have to be able to visualize how you are going to make the information from sources A, B, and C merge together. It makes it very important.

The ability to automatically generate DDL and have the to do it in different flavors (Teradata DDL or Oracle, et cetera), and to be able to fine-tune the forward engineering file so that it comes out the way your shop likes to see the DDL done is critical. It's soup to nuts from the design all the way to implementation. It's really critical.

We find that its ability to generate database code from a model for a wide array of data sources cuts development time. The ability to create one model in your design phase and then have it generate DDL code for Oracle or Teradata, or whichever environment you need is really nice. It's not only nice but it also saves man-hours of time. You would have to take your design and just type in manually. It has to take days off out of the work.

The code generation ensures accurate engineering of data sources especially because you can tweak it.

Development time is another critical issue. If you had to tweak every single piece of code that comes off the line because there's only a one-size-fits-all solution, then the problem would not be worth anywhere near as much as it is. It has the ability to create a customized forward engineering code that you can use to generate your code for your shop so that it always comes out the way you want it.

The product itself is fantastic and it's about the only way to get an enterprise view of the data that you're designing. It's a design tool, obviously. Once you add the API to that where you can automate things, you can make bulk changes. You can integrate your data from erwin into another in-house application that doesn't have access to the data because the erwin data is encrypted. It's been quite a boon to us because we're very heavy into automation, to have the ability to create these ad hoc programs, to get at the data, and make changes on the fly. It's been a wonderful tool.

A data modeling case tool is a key element if you are a data-centric team. There is no way around it. It's a communication tool. It's a way of looking at data and seeing visually how things fit together, what is not going to fit together. You have a way of talking about the design that gets you off of that piece of paper, where people are sitting down and they're saying, "Well, I need this field and I need that field and we need the other field." It just brings it up and makes it visible, which is critical.

I love the product. I love the ability to get into the code, make it automated, and make it do what I want. I would like to see them put some kind of governance over the ability to make changes to the mart tables with the API, so that instead of just using the modeler's rights to a table -- it has a separate set of rights for API access. That would give us the ability to put governance around API applications. Right now a person with erwin and Excel/VBA has the ability to make changes to models with the API if they also have rights to make changes to the model from erwin. It's a risk.

We have a really good relationship with erwin and whenever we come across something and we contact the product developers and the contacts that we have, they immediately put fixes in, or they roll it into the next product. They're very responsive. I really don't have any complaints.

It's a wonderful product and a great company.

I've been using erwin since version 3.0 in the '80s.

It's very stable. It's very mature.

We have about 70 licenses and we have about 70 people using the product full time. I've worked in shops where there were two or three to a dozen. Besides these 70, we also have other parts of the world, shops that have it. It scales right up. I have not worked in a shop where it was either too small or too large.

We have full-time data modelers. We have architects. We don't make a distinction between the data architect and the data modeler. The data architect is designing the enterprise-level view of data and how we use it as a business and then modelers work on specific projects. They'll take this enterprise view and they'll create a project model for whatever it is that we're rolling out.

We've got an architecture person, a modeler person, and we also have some developers who do some smaller database modeling when they had to get out something that's just used in-house. It's not used downstream by the end-user. We have the use of a portal product. Everybody at the company has access to the web portal product. They can go in and see what data has been designed and do impact analysis.

The business analyst will look at it in the web portal to see what the downstream impact would be for them to change a particular name that the company uses for something. They check what the downstream and upstream implications are. Then, the developers use our DI tools for creating the mapping from the source system to the target system. Our data stewards use the tool for the business glossary and for how we define things. Every part of the company that deals with data uses eriwn.

Customer service is fantastic. I know a lot of the guys by first name that work in tech support.

When we have a problem, typically we're broke because we have people here on staff who answer most of the questions and most of the problems. If we have a problem, it's a big problem. They put us straight through and they handle us right away.

I've used four different data modeling tools. Every modeling tool has its strong point but there's none of them out there that are as robust to me as erwin. If I have to choose one tool, it's going to be erwin, especially since I've gotten into the API and I know how to use it. Some of the things the other tools add in terms of being able to manipulate the underlying metadata, erwin has with that API. I won't say they now have it. They've had it since day one, but I've just picked it up in the last year or so.

The setup gets more complex every time. Especially with 2019, they completely changed the interface and that was another learning curve. But for the most part, if you know data modeling, you can find the logical task that you want to do within the physical form and menus of the product. I didn't find the learning curve so bad because I was already a data modeler.

I started the upgrade process today, as a matter of fact. We just got the software installed on a Mart, and I'm going through the new features. I'll play with it for a week. Then we'll get other testers to actually do some formal testing for a week. And then we'll put in our change because we're a large shop. It's around a month cycle to get an upgrade in place. That's if there are no problems. If we come across something that tells us that we can't use this product until this is changed or fixed then it's a stop. For the most part, a happy path, takes around a month in a large shop like ours.

As far as the upgrade itself on dev, it took maybe an hour to upgrade the Mart. And it took me maybe an hour to upgrade the desktops that we use for testing.

We've been doing upgrades for years. I'm been involved in it with multiple companies and it's what I do here. We have a cycle, a strategy, and a checklist that we go through for every upgrade.

The first thing we do is we have a development system. We have virtual machines that we set up, so it's not on anybody's particular desktop. We upgrade the product and then one person will go through and I'll look at the new features and I'll see, number one, if we need the new features. Number two, if there is anything in these features that will break what we're doing today. Those are the first things I look at. If we pass those first two tests, then I start looking at the features and check what we are going to have and what it is going to involve in terms of training the user. We check how it is going to impact the modeler that's actually down in the trenches.

I've got to do the training materials and then the next thing is we have a warranty period. We have a group that pushes the software to the desktop. We have a special day that we roll it out. And then we have a warranty period where we set a virtual call that anybody could sit in if they have a problem. We have a virtual call so that if anybody, when they come in on Monday morning, can't get into the product, or if they're having any problems with that at all, we're right there to answer their questions. We allow for that for the first week. After that, we turn everybody loose. Of course, it doesn't account for the physical part of backing up the database, doing the install, validating over the weekend, and all that stuff. It's just the standard software upgrade stuff.

We implement in-house, but always have access to a World-Class vendor.

I wouldn't know how to measure ROI. I can only say that the alternative is spreadsheets, typing, visually inspecting things, never being able to integrate, never being able to communicate. I can't give an ROI, but I can say that I wouldn't want to work in a shop that didn't have a data modeling data tool.

erwin's my first love. I know that I have been using it long enough that I am under the covers and I know it backward and forwards. It's the one I prefer.

I don't deal with pricing or licensing here. I know that you can get a per-seat license. You can get concurrent licenses. To me, if you're a full-time modeler, you need a per-seat license. If you're a developer or a data steward, you use it a couple of times a day, maybe a couple of times a week, you can have concurrent licenses so that a group of five people will share one license. If someone's using it you can't, but if it's free then you can go ahead and use it, or you can lock it, or whatever. There are different ways of licensing it.

The one thing that having a CASE tool does is it takes the drudge away from modeling. You get to actually think of what you're doing. You think about the solution and not how you are going to keep track of what you're doing. It frees you from a lot of mechanical things that are part of keeping track of data modeling, and it allows you to do the thinking part.

There's not a lot of documentation on the API. You're pretty much going to have to teach yourself. If you have a specific problem where you've gotten to a certain point, you can always touch base with the guys at erwin and they will help you to get little snippets of code. But if you're doing things like we have, which is to write a full-blown application to extract the data or to make changes to the model, you're pretty much going to have to learn it on your own. That's just the one drawback of the API but if you're a programmer and you want to DM like me, it's a lot of fun.

It's a challenge but it's very rewarding to be able to automate stuff that people are doing manually and to be able to hand them a solution.

From one out of ten, I'd give erwin a 9.99. Everything has flaws. Everybody's got these little quirks like I mentioned about the ability to make changes that you shouldn't make. But as far as the product itself, I love it. It's right up there with a 10.

We use erwin to design conceptual, logical, and physical data models for new projects. We use a Forward Engineering tool to forward engineer data models into new database structures. We use the reverse engineering tool to bring databases into data models and erwin. We also generate HTML reports of the models to share with our customers.

Whenever we do have a new project that requires a new approach, we do try using erwin for it. For example, if we have an XSD message file, then we would try to see if there is a way to get that into erwin for better visibility of the structures that we have to work with.

The product has helped us standardize our data modeling efforts across the enterprise in regards to visuals and naming. We also use the Mart Tool from erwin, which allows us to store our data models in a centralized repository, which gives everyone visibility on what is out there and how it is all related.

We discuss existing and new business requirements with business users, data architects, and application developers to figure out how to capture and visualize concepts in their relationships. One thing we do have standard in all of our models is that we use the information engineering notation. This is standard across our enterprise. We do use a diagram hierarchical layout to help visualize things, especially when we reverse engineer a database, as we want to have some sort of a clear visual layout of things.

We find a few of erwin tools most valuable:

• The Bulk Editor lets us easily make a lot of similar changes within our data model.
• We use the Forward and Reverse Engineering tools to help us speed things up and create things that would have to be done otherwise by hand. E.g., getting a database into a data model format or vice versa.
• The Report Designer is extremely useful because we can create reports to share with our business users and have a business discussion with them on how things work.

We find the text manipulation through the Bulk Editor to be extremely helpful. There were times where we had a set of entities which were not following our standards. With the help of the Bulk Editor, we were able to form those names with a few Excel formulas to follow our standards.

The Reverse Engineering functionality is good and easy to follow. It works really well. For the most part, we have been able to get any database to work with our data model format.

We quite heavily use the templates that exist to apply our standards to the data models created by our data modelers. We are able to use the templates to apply things like Naming Standards, casing on names, and colors to all our data models without having to be on top of it.

Complete Compare is not user-friendly. For example, the save known changes as snapshot does not work as expected. We are unable to find the exported files in our workstations at times. Complete Compare is set up only to compare properties that are of interest to us, but some of the differences cannot be brought over from one version of the model to another. This is despite the fact that we are clicking to bring objects from one place to another. Therefore, it's hard to tell at times if Complete Compare is working as intended without having to manually go into the details and check everything. If it could be redesigned to a degree where it is easier to use when we bring things over from one site to another and be sure that it's been done correctly, that would be nice to have. We would probably use the tool more often if the Complete Compare were easier to use.

The client performance could be improved. Currently, in some cases, when we delete entities it causes the program to crash. Similarly, for Mart's performance, we need to reindex the database indexes periodically. Otherwise browsing through the Mart, trying to open up or save a data model takes unusually long.

There are several bugs we discovered. If those were fixed, that would be a nice improvement. We encounter model corruption over time, and it is one of those things that happens. There is a fix that we run to repair this corruption by saving the model as an XML file or to the Complete Compare tool. If this process could somehow be automated, having erwin detect when a model is corrupted and do this process on its own, that would be helpful.

There are several Mart features that could be added. E.g., a way to automatically remove inactive sessions older than a specified date. This way we can focus on seeing which users have been utilizing our central repository recently, as opposed to seeing all of what happened since five years ago. This would be less of a problem if the mart administrator did not have trouble displaying all of the sessions.

On the client side, there are some features that would come in handy for us, e.g., Google Cloud Platform support or support for some of the other cloud databases.

If we had a better way to connect and reverse engineer the databases into data models, that would help us.

Alter scripts can be troublesome to work with at times. If they can be set up to work better, that would help. On the Forward Engineering side of things, by default, the alter syntax is not enabled when creating alter scripts. We strongly believe this is something that should be enabled by default.

On the Naming Standards (NSM) side of things, there is a way in erwin to translate logical names into physical names based on our business dictionary that we created. However, it would be nice if we could have more than one NSM entry with the same logical element name based on importance or usage. Also, if erwin could bring in the definitions as part of the NSM and into a model, then we could use those definitions on entities and attributes. That would be beneficial.

We have been using it for at least 15 years, a very long time.

Overall, the server is mostly stable. After we implemented the reindexing fix on our database, everything works pretty well. On the client side, it is mostly stable, but sometimes it's not. There are certain actions that cause the client to crash. This has been much less of the case since we switched to the 64-bit version of erwin, which has been a great improvement.

We have found erwin’s code generation ensures accurate engineering of data sources. We haven't seen any issues. We pass our code off to DBAs to implement. Therefore, the DDL that we generate gets passed up to the DBAs who will add some physical features and may add some performance indexes, then we will reverse engineer that information and have that in our data models.

For our bug related issues, we have been given the recommendation to upgrade to the latest version. We are in process of doing that and will see how that works out. We also submitted some other things through erwin's idea board. There are a few issues that we haven't reached out to erwin on yet.

Currently, we have a team of people who take turns helping out other users. They figure out how to do different things. If there is a server side issue, we do have several people as well who will look into that. In the past, we did manage a lot with one person. However, we realized it was quite an undertaking. You either need one fully dedicated person to look into this or several people to take turns.

We have a Windows Server and a SQL Server database. Therefore, we have SQL Server dedicated staff to help us with any SQL Server issues and Windows support staff who help us with any Windows issues. We don't generally have any issues with erwin. From a technical support side, we do have a support staff if we were to run into any issues. Our team of five data modelers are pretty well-experienced with both the tool, Mart, and any sort of communication issues that we might have to deal with, e.g., if the SQL server went down, then these folks would be the liaisons to the SQL Server team.

Given our mostly constant user base and constant growth of new data, our impressions of the scalability are great. Currently, we have about 2000 models in the Mart repository. Reaching this capacity has slowed down interactions with the Mart as opposed to when we had a fresh Mart. When we first started using the Mart server, it took about two seconds to open things like the Catalog Manager or Mart Open dialogue. Now, it takes around 10 seconds to do that part. For the most part, it seems to be pretty scalable. We've been able to continue using the tool given our large volume of models.

There are 35 to 40 users plus some occasional DBAs who use it to tweak any of the DDLs that they might want to pull.

We are able to develop our data models for mission-critical tasks with the solution’s configurable workspace and modeling canvas. We have 20 enterprise data modelers. We are mostly working on the standard RDBMSs: SQL Server, Db2, and Oracle. We also use some cloud technologies, like GCP, Azure, and Couchbase. Then, there are approximately another 15 data modelers which work exclusively in Oracle Business Intelligence from a data modeling aspect. This is for dimensional repository and data warehouse stuff. Therefore, we have about 35 to 40 data modelers in our organization for pretty much every major project that passes some sort of funding gate. Anything that is mission-critical for our organization will come through one of our two managers, depending on whether it's relational modeling or dimensional modeling. All of the database designs come through these two groups. There are some smaller database designs which we may not be involved with, but all of the critical application work comes through these teams. In regards to focusing on mission-critical tasks, we really wouldn't be able to do it without a tool like erwin. Since we are all very well-trained in erwin, it is the tool that we leverage to do this.

Erwin generates the DDL for all our projects. We rely on the tool for accuracy as some of our projects have hundreds of entities and tables.

When it is bug related, we get a bug fix or are told to upgrade to the latest version. This has worked out in the past. Where it is question related, we have been pretty happy with their Tier 1 support's responses. We will receive some sort of a solution or suggestion on how to proceed in a very timely manner.

We would like support for JSON reverse engineering. That is something which is completely missing, but is something we have been working with quite often recently. If erwin could support this, that would be incredible.

On the client side, the setup was mostly straightforward. It was a matter of going through the installer, reading a little bit, then proceeding to the next step. In the end, the installation was successful.

On the server side, it has been a bit more complex. We did have some documentation provided by erwin, but it wasn't fully intuitive nor step-by-step. Some things were missing. It was enough to get started, then figure things out along the way.

On the client side, it takes five to 15 minutes to do the installation or upgrade to a newer version. On the server side, from the moment we backed up everything on the server and disabled the old mart application, the upgrade took about two hours. If you include all the planning, testing, and giving support users enough time to do everything, the upgrade took about three months. In general, these are the timeframes we experienced through in the past.

We simply used the documentation provided by erwin. Between the few of us that worked on the upgrade at our company, we had enough of a technical background to be able to figure out things out on our own. There were five to 10 people who worked on this initially:

• We had one person who helped with the database side of things.
• We had another person do everything on the application server.
• To test out of the different features of erwin in the new version and ensure that the existing features worked as intended, we involved several additional people from our team.

We go through a pretty rigorous testing procedure when we bring in a new release of any software like this. Although it's not affecting customers directly, it certainly affects 35 to 40 people. Therefore, we want to ensure that we do not mess them up by not having something work. Normally, we go through this with any product. We first install it on a test environment and have a bunch of folks jump on. This is to ensure everything is working the way we want and work out all the kinks when setting up the production server before we move it into production.

It is an invaluable tool for us. It has been part of our data governance process in regards to database design for at least 15 years.

The amount of time saved is proportional to the amount of changes in the databases that we are implementing at any time. The more code we generate (because the model is bigger), that saves us more time because we don't have to write everything up manually and check to make sure that the code is correct. If we had to give a number, this saves us anywhere from minutes to hours of work. The time frame depends on the data modeler, as some data modelers generate more code than others. Therefore, it could be on a daily, weekly, or monthly basis and depends on the project. Some projects are in maintenance mode and not going through a lot of changes. It is way easier to use this solution because then we have a data model to reference for something that was developed approximately two months ago and somebody can just pick it up versus if someone had to generate changes to a database without a data modeling tool.

The tool certainly makes the data modeling staff more productive than if they did not have a similar tool. Without erwin, our jobs would be a lot more tedious and take a lot more time.

We evaluated IDERA two years ago and decided to stay with erwin mostly because the staff is mostly familiar and comfortable with the tool. We think that was the overriding factor. The other thing would be converting from erwin to IDERA would be a major undertaking that we just weren't prepared to do.

The fact that it can generate DDL is a major advantage over something like Visio, where you can also do a database diagram. We don't have a Visio version that would generate DDL, so I'm assuming it doesn't, and any tool that can generate code for database definition will certainly have an advantage over a product that doesn't.

I would certainly recommend this product to anyone else interested in trying it out. The support from the vendor is great. The tool overall performs well and is a good product to use.

Having a collaborative environment such as the one that erwin provides through the Mart is extremely beneficial. Even if multiple people aren't working on a single model, it's nice to have a centralized place to have all the models. It gives us visibility and a central place to keep everything in one place. Also, it supports versioning, which allows us to revisit it at different points in time to go back to in the model, which is really helpful.

We do not use erwin to make changes directly to the database.

We have no current plans to increase our usage of erwin other than adding more models.

We would rate the solution overall as an eight (out of 10).

erwin Data Modeler does conceptual, logical, and physical database or data structure capture and design, and creates a library of such things.

We use erwin Data Modeler to do all of the levels of analysis that a data architect does. We do conceptual data modeling, which is very high-level and doesn't have columns and tables. It's more concepts that the business described to us in words. We can then use the graphic interface to create boxes that contain descriptions of things and connect things together. It helps us to do a scope statement at the beginning of a project to corral what the area is that the data is going to be using.

Then we do logical data models, which are completely platform-independent. They're only about datasets, the owned attribution, and different key analyses to determine what primary keys we want.

And then we do database designs, which relates to the physical data models. 

We also do reverse-engineering where we are capturing the catalogs of existing systems, or purchased software, or even external vendor datasets. They send us data sets and we can reverse-engineer what they send us, especially the backup snapshots where a vendor in the cloud will send data as a backup restore. So to help the documentation for the reporting team, we do reverse-engineering so that they know what the table and column structure look like, along with sizing, nullability, and keys and constraints.

erwin is on-prem. We have the Workgroup Edition, which means that we don't just have client-side software. We have client-side software that stores the data models back into a database which is on an on-prem server.

When I got to my current company two years ago, it didn't have any collection of its data assets into reporting services. If someone wanted to know where a social security number was in all the databases, they had to download all of the structures and do all of the research. I came in and did a full production-environment, reverse-engineer library. Once I did that using erwin front end, I could help the CCPA team find the PII data by simply doing Workgroup Edition Data Mart reports that crossed all of the environments. 

The cool thing about that is that the erwin models will bring in data from a dozen or two dozen different platforms. But once those models are in your Mart structures, you can do your search, looking for something like names of columns, across all of them. So you could be doing a search across Oracle, PostgreSQL and, because it's in your library, you can look at your assets holistically. For us, we went from zero to 500,000 columns of information. You can do that in Excel or in other ways, but this is a very simple way to do it. And you don't need to be highly-trained and skilled. You could actually bring in a college intern and set them loose with creating those libraries for you. Not needing highly-skilled people is one of the great things about erwin. It's very intuitive and it's not hard to use.

At my current company, we're not using it for much custom work, but in my past, the solution's ability to generate database code from a model for a wide array of data sources absolutely helped to cut development time. If you do your design on paper or in an erwin model before the developers start coding, and you review them to make sure that you've got everything in there, you do much less break-and-fix. If you can have an overview model, even for your Agile developers, and say, "This is where we're going," even if you don't deploy at all, it makes it much simpler. You don't have to drop your structures and recreate and reload your test data because you're pretty confident you've gotten your database design right, before people start coding.

erwin improves your standards because your naming standards and your design standards can all be reviewed much easier. You can make sure that misspellings, for instance, don't get all the way to production, or to the point where you have to live with them because people are already coding against them. You can do so much more QA analysis on your structure before it's deployed, if you're using a model.

You could probably use something like Visio to draw boxes and lines, especially for conceptual, very high-level things. But when you're getting down to the database level, where you're building a design and you're creating DDL out of it, or you're going in the other direction where you're reaching into system catalogs and bringing things back, that starts to really require specialization. Visio isn't going to reverse-engineer that for you. Those features in erwin are valuable.

In addition, erwin has versioning so you can keep versions, over time, of those models and you can compare any version to any version. If you're looking at a specific database and you want to see what changed over time, that's really useful. You can go back to a different version or connect that to your change-control processes so you can see what was released when.

With versioning, you can also compare between development environments and production environments. You can see what may not have actually changed or what changes are in the works. It also enables you to do the kind of troubleshooting where you're looking at: Why on this server does this copy of something seem to behave differently than on that server? erwin highlights that really quickly for you. You don't have to closely eyeball your comparison. erwin creates a report that comes back and says what is different. And you can focus on almost anything, from the privileges in the catalog to a data type or a name anomaly. Even for servers that are case-sensitive in their structure, it will tell you the difference between something in all-caps and something that's mixed-case. If you're getting to that level of detail when you're troubleshooting, erwin is great at doing that sort of thing.

In terms of the solution's visual data models for helping to overcome data source complexity, erwin shows you "what is," if you're talking about the physical layer. When it comes to being able to make things clearer and more understandable, it depends on what your structure is. If you've just reverse-engineered SAP, it's abbreviated German. You may need other tools to help you understand it. If you're doing forward work — if you're going from conceptual to logical to physical — erwin is fabulous at letting you change what you see in the graphic. You can change your data model from just looking at primary keys to looking at primary keys and foreign keys, to looking at just the definition of the table in boxes. It allows you to change that visualization depending on your audience. If you're working with the DBAs, you can add metadata and it expands the box showing the visual of the table structure, so you can concentrate on just data types, or you can do data types and nullability and foreign keys, and all different sorts of things. You can do the indexes on top of it as well. You could end up with a table graphic that's the width of your screen if you've added all the details in.

And if it's too hard to look at that way — if you're trying, for instance, to make sure that EmpID Is always a varchar 250 — it also has the ability to take that graphic and move it into what's called the Bulk Editor. That looks much more like an Excel spreadsheet, within a view in your erwin model. You can sort your Excel spreadsheet by column name and see all of the details next to it. That way, everywhere EmpID shows up in that model, it is now in more of a column-row view, and you can easily look at that to make sure that all the EmpIDs say varchar 250. If you see one that's wrong, you can actually change it in the Bulk Editor and it changes it in the graphic automatically, because an erwin model really isn't a graphic, it's much more like a little Access database. So when you change it on one view, it fixes it in the other.

In addition, anybody using erwin to do forward engineering will find the solution's ability to compare and synchronize data sources with data models, in terms of the speed of keeping them in sync, to be almost instantaneous. You can connect an erwin data model to a database and deploy your changes, or you can deploy just delta changes. Or you can deploy one little piece because you've identified one little piece of your model. But most of comparing and synchronizing data sources with data models comes down to people and process. The tool will absolutely help you get there, but it's not going to take on all of the requirements of putting standards and processes in place. If you haven't tied your erwin Data Modeler to your change-control, it can't help you. So it's not a dynamic connection to your servers, it's just a tool that you can use with your environments.

Also, while I'm not configuring erwin, I do have templates that erwin lets me set up to configure models: different templates do colors and domains and prebuilt macros for definitions, based on different things. You don't have to configure erwin. You just have to tell it what sort of a platform you're either going to or coming from. You can also set up some draw templates and customize the colorization of different things. If you want all your primary keys to be red, you can configure that, and set that up as a template.

Finally, the solution's code generation ensures accurate engineering of data sources. With reverse-engineering, I have found it to be completely accurate. I've never found a time when it didn't get the source information correctly into the model. If you're doing a data warehousing project, where you're going from source to target, erwin can produce an extremely comfortable and dependable and trusted graphic of where you're coming from, while you design where you're going to. You know what the data types are, what the nullability is — the structure of the data. You don't know all the characterizations of data values because erwin is not profiling data values. It's just picking up the catalog structure of the tables. But it is completely trustworthy, once you've reverse-engineered it. It has never let me down along those lines.

One of the things I've been talking to the erwin team about through the years is that every data model should have the ability to be multi-language. So along with the fact that I can change, for example, the graphic of the model to look at just the definitions in boxes, or just the key structures in the boxes, I'd love to be able to change the language. When I was working at Honda, it became very difficult to work with the Japanese teams using just one model. You can have two models, one in English and one in Japanese, but that means you have to keep the updates back and forth, and that always increases the risk of something not being updated.

The world is getting to be a very small place, and being able to have one file that has all of that metadata in whatever form you need to read it, is the best way to manage that data. That would be a big change for them and it would be a big change to the Mart structure. It would be a one-to-many on the logical side of the business names, but it would also a one-to-many on the definition side of the tables and the columns and everything else, where you can have notes. I know that it's a big change I'm asking for, and they've had to put it off a little bit, but their business glossary tool now kind of looks at it that way. I'm hoping that the erwin model itself will be able to allow for that in the future.

I've been using erwin Data Modeler from way before erwin owned it; since the '90s when it was Logic Works. That was before it went to Platinum and before it went to CA. And now they're spun off as erwin.

It's a very stable tool. It doesn't have problems with crashing or anything like that.

I've never had a problem with its scalability, especially using the Workgroup Edition, because you keep all of your models in the database. It's not a problem to collect hundreds of different data models. Even scalability on your desktop or in your laptop would be more about the laptop itself, not the tool. It's kind of like Word. It saves the data outside of itself, so it doesn't have that problem.

There was no data modeling tool when I got here two years ago, so it is new to the culture, and this is a 40-year-old company. It is mostly being used with our master data management and our data warehousing, which is still doing a lot of development work. It's being expanded into supporting the data governance initiatives, to do data asset management. And I'm expecting that over time it will be used more for data asset change-control. We use a lot of vendor-purchased products, and being able to see the difference between their table structures before an upgrade and after an upgrade isn't being documented in a model right now, but it probably will be.

Also, the new California Consumer Privacy Act is forcing us to do much more of that data governance and data asset management, as well as data classification, so that we can identify PII data. That's definitely picking up steam.

I use their technical support all the time. Sometimes it's just to ask them — because it's such a rich tool, they move menu items in the upgrades sometimes — "Okay, where did you put it this time?" But they've always been very helpful. They do have live chat on their website. About 75 percent of the time the chat agents can answer my question. If not, they hand me off to somebody. Given the amount of time I've worked with erwin, I almost know all their first names. They've always been very good and have taken care of me.

A lot of the technical staff moved with the tool, so they've stayed intact as it went through buyouts. I've always enjoyed working with the erwin team. They're very supportive, very helpful, and are very responsive to my requests and thoughts.

My current company did not have a previous solution, other than Excel spreadsheets and Visio — nothing that I would call an industry-standard modeling tool.

I was involved with the purchase and installation in my current company. I work with the DBAs so I don't touch the buttons for the installation. But the erwin support team is always a great help. I have never heard from any of the DBAs, during any of my "lifecycles," that installation is anything more than straightforward.

There's all sorts of bureaucracy that happens at a company, and that's true in our company as well. The deployment happened over the course of a couple of days: the installation, the tests, the verification, and making sure that the client-side could connect to the databases. I don't think any of that took too much time, other than getting everybody together to do it.

Our implementation strategy was to work with a very temporary dev environment and then roll it to a prod environment and then drop the dev environment. We don't keep a dev environment full-time because it is just a COTS tool. They do backups and restores just like any other mission-critical data. And we're using a combination of named licenses and concurrent licenses in our strategy so that we can leverage who uses it the most.

As for the number of people involved in an upgrade. I take on the SME role. We have the main DBA who is scheduling the upgrade into the environment. Then we generally have a DBA who is assigned to do the upgrade. And our service desk helps with the deployment of the client-side out to the users. So there are four people involved.

We saw return on our investment in erwin once we got our model library in place across all of our different data environments. Of course, you can always search using your DBA tools to find different things on a server. But once you've got your models in place, you can cross all the servers in your search, because you've pulled all that metadata into one place. It doesn't matter if it's an Oracle backend, an Access backend, a mission-critical Excel spreadsheet. Whatever it is that you have a model of, you can go search for something like a social security number. Just being able to do that, it almost pays for itself. When you think of how much time people spend to try to find things, it's completely amazing.

It depends on how many servers you have, how complex your environment is, and how many of your teams are going to look at stuff. If you have a really obfuscated structure, then you're actually profiling the data to figure things out.

Being able to type in, "Go find column names with SSN in them," it comes back almost immediately. That probably gets you 80 percent of the way to finding that particular aspect. How much time did we spend in the Y2K crisis just to find dates? Just identifying the columns that were going to be impacted was a feat. I keep telling my cohorts that social security number data is going to be the next Y2K. As soon as we run out of numbers, they're going to have to add a digit, but everything is hard-coded to the current span of digits. As soon as the federal government decides that it's going to do that, we are all going to have to go fix it.

The nice thing about having your assets in a database is that the more value-add you've done on your models, the less you have to look at physical names on columns. If you've put your logical or your business names on columns, that's even better.

I could imagine that in very serious research, you're going to cut 80 percent off the time it would take, depending on how complex your environment is. You can get there so much faster. Obviously, it won't give you everything because human beings just don't have it all written down. Or it could be that some nitwit is putting social security numbers into note fields and you don't know about it. But it's going to get you a long way there.

The erwin model is much more like an Access database. The return on investment is that it is a very three-dimensional type of metadata collection about your model. In some of Visio, you can add notes on a little graphic piece. But you can't add multiples. You could approximate multiples with carriage-returns in the block, but you can't categorize your metadata. You also can't add more value about that metadata. One little box on an erwin model can be opened logically and there will be 10 tabs worth of value-add you can put in. You can open the model so that you're looking at the physical side of the house, and still have another 10 tabs that have nothing to do with the logical side, other than that they share the primary key of the little graphic piece that you're looking at.

erwin is so much more flexible. And, with respect to return on investment, it's customizable. erwin has the concept of user-defined properties where if you need to do something special within your models that says something like, "Is this used by this line of business?" you can create flags, or dates, or text, or drop-down lists, and attach it to anything in the model itself. In that way you've created some value-add that is customized to your company's needs. To me that adds tremendous power to the return on investment. You can't do that with just plain drawing tools.

We came up with a two-part concept with our licensing. Our data architects have named licenses that only they can use. We have four named licenses today. But we also bought three concurrent licenses, two that are just for developers and the DBAs, and one that's a "read-only" that anybody can use. It's a little bit difficult for me to tell you how many people use those, but probably no less than 10 and possibly upwards of 25.

We pay for maintenance on a yearly basis. There are no additional costs for the Workgroup Edition, which has the server component. That is the edition where you can save your models back to a database, which we installed on SQL Server, but I think you can install it on any of several different platforms.

Our company looked at two others. Because I have worked with erwin for so long, I wanted to make sure, when I came in, that my current company got the opportunity to make its choice based on what everybody's needs were here. We did a full vendor tool assessment back then. Although I don't have it in front of me, I know we looked at Embarcadero and it may be that we also did the highest level of Visio, so that between them we looked at a very high-grade tool and something that would just get us by. 

When I got here, the DBAs had already put acquiring an erwin license into their next year's budget. They had already made that choice. But I took us all the way back to doing a tool compare because I wanted to make sure that everybody got the opportunity to weigh in on the choice that was made.

A lot of the difference between erwin and other products was the licensing and pricing structure for maintenance. Some of it was the inter-connectability with other tools. erwin does a really good job of building bridges between many different tools. Part of it was also its ability to be very sustainable because it had the Workgroup database backend, which Embarcadero has as well, but Visio does not. That was part of the decision point: whether we wanted to go with something really small and move up to a more industry-standard tool, or just take the opportunity to bring in a couple of licenses. We brought in a smaller footprint last year, and we added a few more licenses in 2019.

The primary reasons that erwin was selected were that it was much more affordable for us and it was easily maintainable.

Take the time, especially if you're going to use Workgroup, but even if you're using desktops, to figure out how you're going to manage the models. They need to have a naming convention. They need to have a directory organization that makes sense to you. They need to have change-control, just like code. You need to figure out how you're going to use it because once it gets past 50 models, finding something and knowing how to change it and where to change it and where to publish it back out is going to be your biggest headache. You need to think long-term. It's easy when you just have a few models. As soon as you have 1,000 of them, unless you've thought ahead, you're going to have a huge cleanup problem.

The biggest lesson I take away from using erwin Data Modeler is that we should all be doing much better library sciences with our data assets than we do. erwin is a great tool to capture your library sciences. It can tell you what you need to know about a piece of data, or a row of data as a dataset in a table, or a collection of tables. You can add information not just about single things but collections of things. 

We should have many more people whose job it is to add that value. Right now, companies still mostly use erwin for custom development and it needs to be much more built into documentation of any type of data. I use erwin to do data models of reports and of API calls, for example. Any data set, to me, qualifies as needing a model so that you can tell what data elements are in it and what that dataset is used for.

Through all the years, erwin has done a great job of making things better and better. There are always things that we're talking about in terms of improving it, but the fact that it's now starting to integrate better with data governance-type tools so that all of your definitions can move to more of a glossary form, rather than just being in the models, is tremendous. The more that that's integrated back and forth, the better it's going to be.

Out of all of the modeling tools, erwin is a 10 out of 10. It hits all the high points for me. There are some pieces of functionality that competitors come up with, maybe a little bit earlier, but it's a leapfrog-type of thing. Every time the vendors find that something is needed in the world of modelers, they all start to bring it in. I find erwin to be very responsive to those needs. So now, erwin has NoSQL modeling aspects in the tool and they're connecting with their own suite of data governance tools. That means you can push definitions to your data governance tool or bring them back from your data governance tool. It's starting to become much more of an integrated solution, rather than just a standalone.

We use the product for data modeling. 

The solution is good for organizing the data and the scripting part is very powerful. It's easy to create technical scripts for models. 

The solution's reporting side needs to be improved. 

I have been using the solution for three years. 

The solution breaks down sometimes. 

I think the solution's cloud version is better because things become slower when the model grows bigger. 

The product's technical support is fast. 

Though the solution is not cheap, it's worth the money. 

I would rate the product a seven-point five out of ten. 

We used this solution to upload and document our database models from the legacy systems.

The principal feature that I liked is that the solution has a very graphic interface.

I think the interface sometimes looks old-fashioned when compared to other solutions, so maybe that can be improved. 

Also, I would like the solution to be more user-friendly to deploy.

After those initial problems, the solution became stable.

The solution only works with one server and one database, so I don't think it's scalable enough.

The solution has a good support center. They provide responses quickly, in about a day. 

The solution was a little hard to set up. We had to request help from our provider because we had some technical problems with getting the solution to work. There were some problems with configuration, and it took about three months to get the solution working.

My advice to those considering this solution would be that they should first evaluate what they need. I suggest they maybe do a POC to evaluate their use cases and then work at finding a solution, and run all the necessary tests before starting to work with the solution.

I would rate this solution as a seven out of ten.

We use it in order to create models, do some reverse engineering in the case of existing databases, and for comparing models, e.g., what is in the design vs reality.

It provides us a visual of the database, which helps me with the complexity of the models. We can know if someone made changes to anything, which is very important from a development perspective. It helps us maintain control of the work.

We had some data integration projects, where we needed to integrate it for about 100 databases. Doing that manually is crazy; we can't do that. With erwin, it was much easier to identify which tables and columns could be used for the integration. That means a lot in terms of time and effort as well as my image to the customer, because they can see that we are providing value in a very short time.

The solution's code generation ensures accurate engineering of data sources. This accuracy affects our development time a lot. It is very easy to go into the graphical model to change something, e.g., generate scripts. It now takes minutes (less than an hour).

The ability to collaborate between different members across the organization is the most valuable feature. It gives us the ability to work on the same model, regardless of where we are physically.

I like the accuracy. It is very precise.

I am not so happy with its speed. Sometimes, it can have problems with connections.

erwin's automation of reusable design rules and standards is good, but it could be better.

About 30 years.

It is pretty good. I haven't had any problems with crashes, etc.

We have a consultant who is responsible for the maintenance.

The solution's scalability is good. However, there isn't a clear explanation of how to go from 10 to 20 users, which is something that customers ask us.

In my company, there are currently five data managers who use erwin.

I like their technical support. They try very hard to solve the problem.

They are not supporting old versions of some databases anymore, so I don't always have the tools that I need. I would like them to keep the support for the older versions.

The standard edition is quite straightforward to set up. It is just clicking, "Next, Next, Next." This takes less than an hour to set up.

It gets complicated when we set up the group edition. We need to start a database. Sometimes, erwin support is needed for the setup. The setup for the group edition can take two days to a week, depending on the database.

We also sell erwin to some of our customers. Usually, we create some sort of implementation steps to ensure that it will work.

We have seen ROI in terms of time, e.g., consulting time and the ability to answer customers faster. This has improved the image of the company.

The solution’s ability to generate database code from a model for a wide array of data sources cuts development time from two weeks to one day or even hours. This is one of the features that I like.

The price should be lower in order to be on the same level as its competitors.

I have worked with Toad, Sparx, and the free version of Oracle Data Modeler. erwin DM's competitors are cheaper, but the look and feel of erwin is more user-friendly, professional, mature, and enterprise level.

I recommend using erwin Data Modeler. You should have a good business case to convince the finance team, as the price is high for Latin America.

I would rate this solution as nine out of 10.

My previous employer's use case was around data warehousing. We used it to house our models and data dictionaries. We didn't do anything with BPM, etc. The company that I left prior to coming to my current company had just bought erwin EDGE. Therefore, I was helping to see how we could leverage the integration between erwin Mapping Manager and erwin Data Modeler, so we could forward engineer our models and source port mappings, then mapping our data dictionary into our business definitions.

We didn't use it to capture our sources. It was more target specific. We would just model and forward engineer our targets, then we used DM to manage source targets in Excel. Only when the company first got erwin EDGE did we start to look at leveraging erwin Mapping Manager to manage source targets, but that was still a POC. 

As far as early DM source specific, we didn't do anything with that. It was always targeted. 

It improved the way we were able to manage our models. I come from a corporate background, working for some big banks. We had a team of about 10 architects who were spread out, but we were able to collaborate very well with the tool.

It was a good way to socialize the data warehouse model within our own team and to our end users. 

It helped manage some of the data dictionary stuff, which we could extract out to end users. It provided a repository of the data warehouse models, centralizing them. It also was able to manage the metadata and have the dictionary all within one place, socializing that out from our repository as well.

Typically, for an engineer designing and producing the DDL out of erwin, we will execute it into the database, then they have a target that they can start coding towards. 

• Being able to manage the domains.
• Ability to standardize our data types and some common attributes, which was pretty powerful. 
• The Bulk Editor: I could extract the metadata into Excel (or something) and be able to make some mass changes, then upload it back.

We use the macros with naming standards patterns, domains, datatypes, and some common attributes. As far as other automations, a feature of the Bulk Editor is mass updates. When it sees something is nonstandard or inaccurate, it will export the better data out. Then, I can easily see which entities and attributes are not inline or standard. I can easily make changes to what was uploaded to the Bulk Editor. When taking on a new project, it can save you about a half a day on a big project across an entire team.

The Bulk Editor needs improvement. If you had something that was a local model to your local machine, you could connect to the API, then it would write directly into the repository. However, when you have something that is on the centralized server, that functionality did not work. Then, you had to export out to a CSV and upload up to the repository. It would have been nice to be able to do the direct API without having that whole download and upload thing. Maybe I didn't figure it out, but I'm pretty sure that didn't work when it was a model that sat on a centralized repository.

I have been using erwin since about 2010. I used it last about a year ago at my previous employer. My current employer does not have it.

We only had one guy who would keep up with it. Outside of the server, as far as adding and removing users and doing an upgrade which I would help with sometimes, there were typically only two people on our side maintaining it.

There are about 10 users in our organization.

There were a couple of little things that you had to remember to do. We ran into a couple of issues more than once when we did an upgrade or install. It wasn't anything major, but It was something that you really had to remember how you have to do it. I

t takes probably a few hours If you do everything correctly, then everything is ready to go.

There were two people from our side who deployed it, a DBA and myself. 

We didn't go directly through erwin to purchase the solution. We used Sandhill Consulting, who provided someone for the setup. We had used them since purchasing erwin. They used to put on workshops, tips and tricks, etc. They're pretty good.

Once you start to get into using all the features, it is definitely worth the cost.

With erwin Mapping Manager, which I have PoC'd a few times, it was something that I'd always get to produce ETL code. I have also used WhereScape for several years as well, and that type of functionality is very useful when producing ETLs from your model. It provides a lot of saving. When you're not dealing with something extremely complex, but just has a lot of repeatable type stuff, then you get a pretty standard, robust model. That's a huge saving to be able to do that with ETL code.

The ability to compare and synchronize data sources with data models in terms of accuracy and speed for keeping them in sync is pretty powerful. However, I have never actually used the models as something that associates source. It is something I would be interested in trying to learn how to use and get involved with that type of feature. It would be nice to be able to have everything tied in from start to finish.

I am now working with cloud and Snowflake. Therefore, I definitely see some very good use cases and benefits for modeling the cloud with erwin. For example, there is so much more erwin can offer for doing something automated with SqlDBM. 

I would rate this solution as an eight out of 10.