erwin Data Modeler vs. Tableau Desktop vs. Talend Data Fabric

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

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

Truly trusted contact center where the effective solution is always guaranteed. It is not a one-off fix to a specific data integration or management problem. It is a permanent and scalable solution to manage all of your data under a unified environment. Easy to use, great performance, used it for our internal data warehouse. Easy to build and connect to our data sources such as Salesforce, Netsuite, and Marketo.

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

• 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

• It supports a wide variety of connectors (Systems/endpoints)
• It provides great flexibility for developers as it not only has a lot of predefined ready to use the function but also provides the ability to use complex java code within the platform. Great tool if you have good developers available.

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

• 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

• The print and export functionality are missing in the Community version which frustrates a lot of our clients as well as internal users.
• The learning curve is very steep for all Talend products including DQ.
• Lack of easy to create workflows for jobs that can be repeated.

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

Lack of report export and publication! Steep learning curve!

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.

At this moment the usability of Talend Data Quality is optimal, too bad I cannot say the same in the first three months, it was always a problem due to its steep learning curve, but what matters is being able to use it effectively at this precise moment.

Incentivized

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

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

Talend Data Quality gave us direct help in the learning process and prevented us from taking many more months to adapt and I appreciate this from the heart, I think that thanks to the support we can have very detailed reports that help increase the use of Talend Data Quality in the company.

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

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

The engine with which it works to process a lot of information is striking, the comparison also being the connectors it has for different RDBMS, which other tools do not count as they are GNU licenses or community editions. The friendly and intuitive environment is what catches the eye. that's why I choose Talend over any other tool

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

• 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

• Definitely simplified the development efforts on our end in doing the data integration, saving lots of human hours.
• Small company, so cost could be a problem for these services, but works so far.

Incentivized