Dataiku vs. IBM InfoSphere Information Server vs. Informatica Intelligent Data Management Cloud

Dataiku is an awesome tool for data scientists. It really makes our lives easier. It is also really good for non technical users to see and follow along with the process. I do think that people can fall into the trap of using it without any knowledge at all because so much is automated, but I dont think that is the fault of Dataiku.

Incentivized

Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.

Informatica Cloud is a great tool for use when data must be formatted consistently. Once configured, it is very robust and reliable. It is also well-suited for an organization without a robust IT staff to maintain a full server infrastructure. It offers a cost-effective approach to high-quality data integration for even the largest organizations. Organizations without staff experienced in data analytics may find it challenging to take advantage of the more complex results of this tool.

Incentivized

• Allows users to collaborate and monitor individual tasks
• Caters to both types of analysts, coders and non-coders, alike
• Integrate graphs and plots with visualization tools such as Tableau

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• IIS best for ETL ,not ELT , and many and diffrent source systems.
• It also can process big data , unstuctured data
• It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems

Incentivized

• Once the secure connection is established it’s quite easy to operate and create new jobs. The controls are simple, and we appreciate the fact there are not a lot of complex fine-tunings required. Navigation is also easy, and we enjoy the ability to open multiple tabs in the browser to work on multiple projects.
• The monitoring functionality works well to help track the progress of the jobs, again, without too much complication. In a fast dev environment, speed is essential and we quickly seeing the status/progress of jobs as well as any errors if the jobs fail helps us maintain speed.
• The web interface is a lot easier to interact with than the client/on-prem version. Putting much of the heavy lifting of interacting with the tool onto the shoulders of the browser makes it easier to keep multiple sessions open and get in/out quickly without having to VPN into the office.

Incentivized

• The integrated windows of frontend and backend in web applications make it cumbersome for the developer.
• When dealing with multiple data flows, it becomes really confusing, though they have introduced a feature (Zones) to cater to this issue.
• Bundling, exporting, and importing projects sometimes create issues related to code environment. If the code environment is not available, at least the schema of the flow we should be able to import should be.

Incentivized

• I would be nice to have a new web development environment for DataStage.
• Connectivity Packs such as Pack for SAP Application are a little pricey.
• It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.

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• The User Interface can be a bit difficult to get in initial stages.
• Error messages are hard to understand which sometimes takes a lot of time for the resolution
• Cannot Implement complex SQL queries which should be fixed in future release.

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• Scale of implementation
• IBM techsupport

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The user experience is very good. Everything feels intuitive and "flows" (sorry excuse the pun) so nicely, and the customization level is also appropriate to the tool. Even as a newer data scientist, it felt easy to use and the explanations/tutorials were very good. The documentation is also at a good level

Incentivized

The open source user community is friendly, helpful, and responsive, at times even outdoing commercial software vendors. Documentation is also top notch, and usually resolves issues without the need for human interactions. Great product design, with a focus on user experience, also makes platform use intuitive, thus reducing the need for explicit support.

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I've never had trouble getting into contact with Informatica's support for technical help. I give it a nine because it does pretty well for mid to enterprise-scale workflows.

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Anaconda is mainly used by professional data scientists who have profound knowledge of Python coding, mainly used for building some new algorithm block or some optimization, then the module will be integrated into the Dataiku pipeline/workflow. While Dataiku can be used by even other kinds of users.

Incentivized

DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS

First, the wizard is easy to use making the learning curve for simple ETL tasks nice. Second, since Informatica is mature there are a good variety of connectors available. Finally, we have driven some fairly complex ETL solutions using only the cloud.

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• Customer satisfaction
• Timely project delivery

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• Productivity of the development of integration processes.
• Better documentation and governance.
• Reduce training costs of various technologies.

• Cut costs on the number of staff we need for data import.
• Cut costs for automation that can be done for data that no longer has to be manually imported.
• We've saved countless dollars by eliminating duplicates in our system with this tool.

Incentivized