IBM Watson Studio on Cloud Pak for Data vs. Microsoft Azure IoT Hub

It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.

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We are using the Azure IOT hub for solving the multitenancy problem within our research project. We are consuming data from various resources and communicating it with different devices on our hybrid cloud. We also use Azure IoT as a bridge between two business Intelligence sources which are really hard to connect devices.

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• Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
• SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
• Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
• Estimator validation lets data scientists test and prove different models.

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• Massive registration and deployment of new devices.
• Easy integration with other Azure services.
• Handling security if devices.

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• The cost is steep and so only companies with resources can afford it
• It will be nice to have Chinese versions so that Chinese engineers can also use it easily
• It takes a while to learn how to input different kinds of skin defects for detection

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• Hardware and embedded integration could improve or be at parity with competitor.
• Pricing model not as flexible as competitor.

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because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)

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The UI flawlessly merges this offering by providing a neat, minimal, responsive interface

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From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected

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Never had slow response even on our very busy network

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I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path

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Azure IoT support professionals are strong, and always provide timely responses. Vast documentation and examples are available, plus a network of professionals in the market. It's very comparable to the main competitor offer, and easily integrated into the main Azure product offer. Azure IoT is not a new solution, so it is very mature and support can easily address any day to day or architectural concern you have.

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The trainers on the job are very smart with solutions and very able in teaching

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The Platform is very handy and suggests further steps according my previous interests

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It surprised us with unpredictable case of use and brand new points of view

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The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.

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We require Azure integration, data security and simple development. IoT Hub ticked all those boxes.

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It helped us in getting from 0 to DSX without getting lost

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• Could instantly show data driven insights to drive 20% incremental revenue over existing results
• Still don't have a real use case for unstructured data like twitter feed
• Some of the insights around user actions have driven new projects to automate mundane tasks

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• As a student, we are using student program subscription which is cheaper than an individual or business subscription.
• Our school devices our efficiently communicating with each other which has increased the revenue of our school.
• It provides strong and robust cloud communication within the premises which also helped in increased in the school reputation.

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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