IBM Cognos Analytics vs. IBM Watson Studio on Cloud Pak for Data

Our first and most basic scenario was to automatize the creation and publication/sharing of business reports that used to be created manually by employees throughout our organization. Using Cognos for that first use case worked well. The advanced analytics functionalities we used on the aggregated data were also as expected. However, the user interface is not always intuitive, and there is a steep learning curve, so I would recommend Cognos only to large organizations where there is a need for the most advanced functionalities (AI analysis/prediction).

Incentivized

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.

Incentivized

• We use the tool for data modeling as it helps in predictive data analysis for complex data, which is very similar to real-life scenarios.
• Options of customizing & scheduling reports as per our requirements basis.
• Has mobile application which works seamless.

Incentivized

• 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.

Incentivized

• Sometimes there might be performance issues when dealing with large and complex data.
• Although IBM provides full documentation but sometimes it's difficult to find answers to questions and connect with their customer support.
• It relies on external tools for data cleaning, transformation and also for some integration tasks. It can also improve on providing wider range of data sources for integration.

Incentivized

• 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

Incentivized

For an existing solution, renewing licenses does provide a good return on investment. Additionally, while rolling out scorecards and dashboards with little adhoc capabilities, to end users, cognos is very easily scalable. It also allows to create a solution that has a mix of OLAP and relational data-sources, which is a limitation with other tools. Synchronizing with existing security setup is easy too.

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

Incentivized

We have a strong user base (3500 users) that are highly utilizing this tool. Basic users are able to consume content within the applied security model. We have a set of advanced users that really push the limits of Cognos with Report and Query Studio. These users have created a lot of personal content and stored it in 'My Reports'. Users enjoy this flexibility.

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

Incentivized

Reports can typically be viewed through any browser that can access the server, so the availability is ultimately up to what the company utilizing it is comfortable with allowing, though report development tends to be more picky about browsers and settings as mentioned above. It also has an optional iPad app and general mobile browsing support, but dashboards lack the mobile compatibility. What keeps it from getting a higher score is the desktop tools that are vital to the development process. The compatibility with only Windows when the server has a wide range of compatibility can be a real sore point for a company that outfits its employees exclusively with Mac or Linux machines. Of course, if they are planning on outsourcing the development anyways, it's a rather moot point

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

Incentivized

Overall no major complaints but it doesn't handle DMR (Dimensionally Modeled for Relational) very well. DMR modelling is a capability that IBM Cognos Framework Manager provides allowing you to specify dimensional information for relational metadata and allows for OLAP-style queries. However, the capability is not very efficient and, for example, if I'm using only 2 columns on a 20-column model, the software is not smart enough to exclude 18 columns and the query side gets progressively larger and larger until it's effectively unusable.

Never had slow response even on our very busy network

Incentivized

Why is their web application not working as fast as you think it should? They never know, and it is always a a bunch of shots in the dark to find out. Trying to download software from them is like trying to find a book at the library before computers were invented.

Incentivized

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

Incentivized

Onsite training provided by IBM Cognos was effective and as expected. They did not perform training with our data which was a bit difficult for our end-users.

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

Incentivized

The online courses they offer are thorough and presented in such a way that someone who isn't already familiar with the general design methodologies used in this field will be capable of making a good design. The training environments are provided as a fully self contained virtual machine with everything needed already to create the environments. We've had some persisting issues with the environments becoming unavailable, but support has been responsive when these issues arise and straightening them out for us

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

Incentivized

Make sure that any custom tables that you have, are built into your metadata packages. You can still access them via SQL queries in Cognos, but it is much easier to have them as a part of the available metadata packages.

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

Incentivized

In the past Management had used Excel and Workiva capabilities to create the reporting dashboards that were being used to make decisions. Since switching to IBM Cognos Analytics the Company has been much more efficient and decision making has been streamlined. IBM Cognos Analytics was chosen due to its reputation and data visualization capabilities and neither have been wrong.

Incentivized

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.

Incentivized

The Cognos architecture is well suited for scalability. However, the architecture must be designed with scalability in mind from day one of the implementation. We recently upgraded from 10.1 to 10.2.1 and took the opportunity to revamp our architecture. It is now poised for future growth and scalability.

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

Incentivized

• High ROI with well designed solutions. Supported by scalable deployment, robust security model and ability to create valuable content.
• High ROI where well designed data models can be deployed with a common metadata layer to a variety of users and use cases.
• High ROI in an environment that includes a variety of vendors and best of breed products within the overall platform

Incentivized

• 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

Incentivized