IBM Watson Studio on Cloud Pak for Data vs. Microsoft BI (MSBI)

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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Microsoft BI has a lot of features and is a very powerful tool, especially if you have folks on your team that know how to utilize all of its capabilities. To truly unlock all that it can do, it does require people to have a deep understanding of its capabilities. That's where the software really shines. If you are looking for a simpler, more basic reporting tool, there are other programs available that do not require such a steep learning curve.

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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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• Comparatively easy to use compared to other data analytics solutions, collaborating with other colleagues on data work is simple.
• Using Visual Studio for database, ETL, reporting, and analytics development save time and money.
• Transfer of data from one application to another via Excel and comparison of data attributes between applications
• Dashboard functionality, as well as Python support, are available, allowing you to add additional charts and graphs.

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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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• MSBI designs can work on increasing data processing capabilities enough to handle the huge datasets etc.
• It would be a lot better if it is a little low on cost.
• it needs to create opportunities little more than they do regarding customization of some very unique visualization effects

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

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Microsoft BI is fundamental to our suite of BI applications. That being said, Northcraft Analytics is focused on delighting our customers, so if the underlying factors of our decision change, we would choose to re-write our BI applications on a different stack. Luckily, mathematics are the fundamental IP of our technology... and is portable across all BI platforms for the foreseeable future.

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

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The Microsoft BI tools have great usability for both developers and end users alike. For developers familiar with Visual Studio, there is little learning curve. For those not, the single Visual Studio IDE means not having to learn separate tools for each component. For end-users, the web interface for SSRS is simple to navigate with intuitive controls. For ad-hoc analysis, Excel can connect directly to SSAS and provide a pivot table like experience which is familiar to many users. For database development, there is beginning to be some confusion, as there are now three tool choices (VS, SSMS, Azure Data Studio) for developers. I would like to see Azure Data Studio become the superset of SSMS and eventually supplant it.

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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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The product has been reliable.

Never had slow response even on our very busy network

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SQL Server Reporting Services (SSRS) can drag at times. We created two report servers and placed them under an F5 load balancer. This configuration has worked well. We have seen sluggish performance at times due to the Windows Firewall.

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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MSBI natively has a site that allows you to vote on user enhancements and bug fixes. This allows the largest nagging issues to float to the top and the development team can prioritize accordingly. As mentioned earlier, the large community base of MSBI developers assist technical resources in handling technical questions.

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

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This training was more directed toward what the product was capable of rather than actual programming.

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

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I have used on-line training from Microsoft and from Pragmatic Works. I would recommend Pragmatic Works as the best way to get up to speed quickly, and then use the Microsoft on-line training to deep dive into specific features that you need to get depth with.

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

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We are a consulting firm and as such our best resources are always billing on client projects. Our internal implementation has weaknesses, but that's true for any company like ours. My rating is based on the product's ease of implementation.

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 have used the built in ConnectWise Manager reports and custom reports. The reports provide static data. PowerBI shows us live data we can drill down into and easily adjust parameters. It's much more useful than a static PDF report.

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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 SaaS provider we see being able to provide self-service BI to our client users as a competitive advantage. In fact the MSSQL enabled BI is a contributing factor to many winning RFPs we have done for prospective client organisations.
• However MSSQL BI requires extensive knowledge and skills to design and develop data warehouses & data models as a foundation to support business analysts and users to interrogate data effectively and efficiently. Often times we find having strong in-house MSSQL expertise is a bless.

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