IBM Cloud Pak for Data vs. IBM Cognos Analytics

IBM Cloud Pak for Data with Netezza is well suited for clients who require fast, economical analytics processing. It is not designed to be used as a transactional processing environment. For example, a large customer is using it during the point of sale process. That makes little sense in that business case. However, to take analysis to market faster, it excels well in that space.

Incentivized

IBM Cognos Analytics has great scheduling capabilities. A single report can be parameterized (e.g., “Store Manager ID”) and burst to thousands of recipients with their slice of data.IBM Cognos Analytics is a good fit for highly complex, multi-level calculations which can be handled by Report Studio. For example Monthly balance sheet that requires multi step calculation

Incentivized

• Increases our impact by combining BI skills with advanced analytics and machine learning in an easy to use visual interface.
• Visualization and reporting.
• Rapidly provides business -ready data to all users equally.
• Manage data spread across distributed stores and clouds.

Incentivized

• We can make dozens of dispatchers all focusing on different types of workloads.
• Friendly user interface, without the need for coding or complicated editing.
• Highly functionality reporting tools.
• We can easily create trigger when a certain threshold are met sending reports or alerts to needed parties.

Incentivized

• Cannot save changes to some secrets in the internal vault
• Sign-in issues on environments where IAM is enabled
• The Enforce quotas option is disabled

Incentivized

• IBM Cognos Analytics enables customer data segmentation, which is essential for marketing, improving and streamlining purchasing behavior and preferences. This helps companies create more targeted and effective marketing campaigns.
• Our clients Through data analysis, we can identify and observe trends in the behavior of other clients, allowing us to anticipate needs and adjust strategies to avoid consequences.

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.

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.

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

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.

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

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 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

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.

IBM Cloud Pak for Data takes the IBM Cognos solution and provides this on an enterprise cloud platform that can be extended to support better data integration and data science capabilities.

Incentivized

My company selected IBM Congos Analytics because of its advanced features and data representation for data analysis. Its row and column features are very effective for creating dashboards and reports to visualize data. It's chart representation and view format are very attractive and useful for representation.

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.

• We have the ability to access all our data much quicker through the unified search option.
• 30% increase in productivity through the introduction of AI.
• Improved data security and governance.

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.
• API integration is not upto the mark with very limited options.
• Licensing & Maintenance can go from cheap to expensive depending on the scope.

Incentivized