erwin Data Modeler vs. SAP PowerDesigner vs. Tableau Desktop

I have had a chance to use few other data modeling tools from Quest and Oracle, but I am most comfortable using erwin Data Modeler. They understand your data modeling needs and have designed the software to give you a feeling of completeness when you are designing a data model.

Incentivized

SAP PowerDesigner allows our team of data modelers to work and collaborate from a single repository and single data dictionary. This helps enforce consistency as data elements are referenced in other objects. Prior to our use of PD, we might have an element named "ppt" in one table, "participant" in another table and "part" in a third table. By forcing everything to be used from the data dictionary, we avoid these situations because everyone has to go to the dictionary. And we are able to easily do peer reviews on models before they are released because we are collaborating through the use of the repository.

Incentivized

The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).

Incentivized

• Reverse Engineering: I love the way we can import an SQL file containing schema meta data and generate ER diagram out of it. This is specifically useful if you are implementing erwin Data Modeler for an existing database.
• Forward Engineering: We use this feature very frequently. Where we do database changes in our physical and logical data models and then generate deployment scripts for the changes made.
• Physical vs Logical Models: I like to have my database model split into physical and logical models and at the same time still linked to each other. Any changes you make to logical model or physical model shows up in the other.

Incentivized

• Impact Analysis
• The domain structure helps you to handle different data types to unify.
• Moving between from conceptual model to logical model and from logical model to physical model is so easy.
• It also excels at implementation of database vendor-specific physical options.
• The repository structure helps you to use in multi developer and architect based organizations by the check in and check out mechanism.
• It also has a fully configurable naming convention implementation.
• Coloring is simple with format copying and pasting option.

Incentivized

• An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
• Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.

Incentivized

• Cost is the single largest barrier to entry with this tool.
• Would like to see a greater variety of export options available for use outside of the tool, for example as a vector graphic.
• Support has been uneven at times.

Incentivized

• It took some time to figure out how to leverage the power of the repository. Some better examples in the documentation would have been helpful.

Incentivized

• Pricing should be more user-friendly and usage-driven
• Making edits to the production reports is fairly tough and has a vast scope of additional capabilities
• Tableau Desktop should be able to differentiate itself from the Tableau server else there is no major meaning of two different products being offered

Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.

Incentivized

I had a lot of experience using erwin Data Modeler for designing data models. I think it's pretty intuitive and easy to use. It has enough features to represent your database requirements in form of a model.

Incentivized

Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.

When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.

Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast

Incentivized

CA customer support and our account manager have been able to support us with any issues that we have had, from managing our serial keys to issues we logged tickets to resolve. There are aspects of key management that have made it difficult over the years but support usually has worked with us.

Incentivized

We did have to reach out to support to learn how to properly utilize the repository feature and share the data model across many developers. Support was able to help us get this set up correctly. The downside was it took us several weeks before we gave up and contacted support. We should have done that earlier. I would say, however, the documentation wasn't clear on how to do this. So support was a great big help!

Incentivized

Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.

Incentivized

It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.

I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems

Incentivized

Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.

Incentivized

Not listed, but I've only used alternatives built into something like the Squirrel SQL editor. That one is semi-functional but lacking many features and, in some instances, just plain wrong. The only pro there is that it's freely available and works over ODBC. I've tried some of the other free ones like Creately but didn't have much success.

Incentivized

Oracle SQL Developer Data Modeler : Unfortunately this tool only supports Oracle Databases as a target database, but has many features similar to SAP Sybase PowerDesigner. erwin Data Modeler: Has some issues when switching from Conceptual Model to Physical Model, Impact Analysis, and formatting copy and pasting. Vertabelo: Only supports online models and from a governance perspective, it is impossible for me to connect my target database with an online application because of company policy and regulation requirements.

Incentivized

I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.

Incentivized

Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.

• It is difficult to assign a monetary value to it. The initial learning curve was fairly long.
• It allows us to have better support documentation.
• It allows ease of communications between functional units.

Incentivized

• Standardization of models
• Impact Analysis
• Graphical User Interface
• Ease of deployment

Incentivized

• Tableau was acquired years ago, and has provided good value with the content created.
• Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
• Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.

Incentivized