Alteryx vs erwin Data Modeler

• Alteryx does a great job of allowing more beginner Analysts to automate many of their routine process but also allowing advanced Analysts to ability to leverage deep statistical modelling for predictive analytics.
• Given the visual workflow nature of Alteyrx, the learning curve is not steep.
• The Alteryx Gallery allows non-technical consumers to execute complex workflows by leveraging an intuitive web interface.
• Alteryx allows data scientists to bring their own programming language to Altyerx, such as R or Python.

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• 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.

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• Sometimes the desktop version of authoring tool crashes! It's been unstable in the previous versions but gets better. Even if it doesn't crash, it used to be slow or not responding.
• When running several version of database drivers in local machine or server, it is tricky to set up database connections. Often you have to figure out it by googling the problem and solution. There are not many knowledge bases from Alteryx.
• Alteryx project file creates .bak file automatically. It is useful to prevent for the purpose of back up, sometimes it's not necessary. But it is not changeable for some reason. By default, it always creates backups.

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• The main con I can think of is cost.
• It takes time to setup and learn which is an adoption barrier.

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• Alteryx does an excellent job of integrating consumer and spatial data to calculate and visualize things like locations within a certain drive-time radius.
• For visualization purposes I had to move the data to excel for some decent graphs.
• It can become very expensive.

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• erwin Data Modeler had been a great tool for our database development and application DBA teams. The thorough data modeling and release control helps us to back trace any issues which are pointed to us at a later stage in the development cycle.
• Initially, some of the team members saw it as an extra effort to maintain data models while they can simply create scripts without models. But overtime, people have realized how it avoids problems and discrepancies over time.

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