Dataiku vs. SAP Crystal

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.

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Generation of templated reports is the strong suit of SAP Crystal. Allows users to change formats in templates bases on requirement with minimal effort. Automated report delivery requires the user to be aware of sql which cannot be expected from all users. Should support more document export formats and improve the UI for SAP B1 Users

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• 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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• Crystal Reports allows us to create a consistent template for all of our reports.
• Crystal Reports and Server allows us to house a repository for all of our reports to make them easy to find and update when necessary.
• Crystal Reports can connect to a wide variety of data sources.
• Crystal Reports can be a little daunting when first implementing. There are a lot of nuances in learning how to truly master this software and it can be frustrating at times.

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• 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.

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• The export of reports to Excel is very cumbersome and the results are difficult to format.
• The design of reports and the graphical features (e.g. charts) feel quite rigid.
• The learning curve for a non-programmer is incredibly steep, making Crystal a specialty tool.

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We have been using this product for so many years and it has truly become a cornerstone to our business processes when it comes to developing and distributing information via reports. We currently have over 500 reports developed to date over about 30 systems and that will continue to grow as user needs change.

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

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Crystal is very robust, but not always easy to use. It create wonderful looking reports, and so deserves a high rating. However, I have to take a couple of points off for the simple fact that I cannot hand it to a user and expect them to be able to do development with it.

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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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The support community can be difficult to navigate. I've also run into issues with my login. The SAP system has a bizarre mechanism for validating users that requires users to have what is called an S-ID. A basic ID may not give you access to all the features in the portal. The limitation may include not being able to perform a simple task like downloading patches and updates. This isn't a big deal for single user license but for teams it can be a pain.

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Trainer was patient and thorough in going through the basics and willing to answer questions by email after the initial training

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Just like any other implementation: When designing the differing reports, get end users' input, make sure to design the reports so that they display the information that the company requires, in the best and clearest way possible.

Test, test, test, revise when needed, and, particularly, do sufficient training so users are comfortable using Crystal Reports!

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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.

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Crystal reports is useful in case we want to import data from data base . We can write queries in it but Google Charts require to be implemented in our application using code so crystal reports is better than Google Charts.

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• Customer satisfaction
• Timely project delivery

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• It is a decent buy for specific departments in terms of reporting capabilities but updates and cost (frequent) demands are higher with the benefits offered.
• So long as the requirements are not ever changing, with scheduling functionality, it's a handsome tool.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info