IBM Watson Visual Recognition (discontinued) vs. Tableau Cloud

As I mentioned before, it can only be employed in simple basic visual recognition applications. It can be employed in large projects and relying it on completely is not encouraged. It's better to create your own algorithms rather than using it. If you are from a non-programming background, then I may suggest you rely on this and use it to develop simple apps that can predict a few plants and animals.

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If you're using Tableau as the primary BI tool, then Tableau Cloud is well suited to publish and share the results with a wide(r) audience. It is well suited for various degrees of self-service proficiency, from pure consumers of analytical work to more advanced users who can use web editing for smaller or larger adjustments, and even for desktop power users who will publish their work to Tableau Cloud. It has many good ways to organize the content and make it easily accessible via search, favorites, folders, collections ("playlists for your data"), or history ("recents"). It might not be ideally suited if there are many on-prem sources to be used (even though there are options to connect them) or if you have very special requirements regarding custom server setup, which is limited in a shared cloud environment like Tableau Cloud.

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• Food recognition
• High reliability
• Speed

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• Tableau Online is completely cloud based and that's why the reports and dashboards are accessible even on the go. One doesn't always need to access the office laptop to access the reports.
• The visualizations are interactive and one can quickly change the level at which they want to view the information. For example, one person might be more interested in looking at the country level performances rather than client level. This is intuitive and one doesn't need to create multiple reports for the same.
• The feature to ask questions in plain vanilla English language is great and helpful. For quick adhoc fact checks one can simply type what they are looking for and the Natural Language Programming algorithms under the hood parse the query, interpret it and then fetch the results accordingly in a visual form.

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• Not perfect
• Accuracy is doubted and sometimes it may not predict correctly.
• I think it should be improved and should add a few more functionalities.

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• Can be a steep learning curve for new users
• Modeling and building algorithms aren't always intuitive and take some testing/retesting to ensure it's working as it should
• Inability to integrate easily with our HRIS platform. Reports are pulled from HRIS at various intervals and uploaded into Tableau

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I am giving this rating on the basis of its usability in real-time applications and based on the interface to upload negative and positive images to train the AI. But it's not perfect and sometimes its predictions are wrong. On overall usability, it's better if you are planning on working with UI rather than using complex programs and algorithms on your own.

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Based on comments from our clients, I awarded it this grade. Non-technical customers frequently compliment us on the ease with which they can utilize Tableau Online. Usability is rarely a source of contention amongst our customers. Few complaints have come from me as a user of our internal products.

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I have not had any issues that require customer support from Tableau at this time, which speaks well to Tableau. I have taken an online course with Tableau and it was very professional and well done, so based on that I would assume a similar level of quality for their customer service.

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In determining whether to go with Tableau Online versus Alteryx, two important factors stood out in determining our go-to solution. First, while Alteryx is an impressive tool for data cleansing, it did not stack up in terms of data visualization capabilities. Tableau, on the other hand, provided us everything we needed in terms of visualizing our data and analytics. The second factor is cost. Well neither solution would be considered cheap, Tableau was the more cost effective solution for our needs.

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• High cost if models are trained

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• When we release new products, we are now able to quickly see data and toggle between current periods and previous to see performance
• Generating new reports requires less IT time to build
• Data can be shared across many different device types
• We now have integration where our customers can extract data from our software more easily-this was a big ask from our customers

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Independently Invited by TrustRadius

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. More Info