IBM Cognos is a full-featured business intelligence suite by IBM, designed for larger deployments. It comprises Query Studio, Reporting Studio, Analysis Studio and Event Studio, and Cognos Administration along with tools for Microsoft Office integration, full-text search, and dashboards.
$10
per month per user
Metabase
Score 7.9 out of 10
N/A
Metabase aims to bring data tools with the simplicity of consumer products to the crufty world of enterprise business intelligence. Their open source analytics and business intelligence applications connect to most commonly used databases to let anyone in a company ask questions, and create dashboards or nightly emails without knowing SQL. Metabase Enterprise enables the user to embed branded analytics into customer applications.
$85
per month
Pricing
IBM Cognos Analytics
Metabase
Editions & Modules
On Demand - Standard
USD 10.00
per month per user
On Demand - Premium
USD 42.40
per month per user
On Demand - Standard
USD 10.60
per month per user
Starter
$85
per month (includes 5 users, then $5 per user, per month)
Starter
$85
per month up to 5 users
Pro
$500
per month up to 10 users
Growth
$749
per month (includes 10 users, then $15 per user, per month)
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
Metabase is an easy tool to use if you are interested in collecting and aggregating data from multiple platforms. It is also easy to set up and start receiving the data results as a report. It is also easy to integrate with other tools that generate visual reports and take the necessary actions based on the data details.
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.
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.
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.
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.
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 is serving us whatever we're looking for, and we've recommended many organizations to implement it if they want better data analytics as it provides better functionality than we will build.
As a negative it gets difficult to get control over data to be fetch initially.