Glia vs. IBM Cognos Analytics vs. Stratifyd

It is well suited for repeatable user journeys that require a high touch and service environment. Glia excels at providing tools that enable and create engagement, in a diverse form of options and methods. It is fully customizable and integration is better than simple. Glia is probably less suited for an organization that is looking for a self-service engagement tool, not manned by users.

Well suited: Financial reporting - It can handle complex, pixel perfect, muti-page reports with scheduled delivery to stakeholders (like sales report by region on quarterly periodicity) Operational dashboard across departments - It can combine multiple data sources (ERP, CRM, excels etc) with filters, and embedded AI insights Less appropriate: Live dashboards - As stated earlier as well, IBM Cognos Analytics doesn't suit well for live dashboards or event driven data. For ex: live web traffic data or IOT device data, etc Data science - Although IBM Cognos Analytics is great tool for data exploration but it should not be used as a substitute for Python or R, which has edge over advanced modelling and stats based workflows like predictive modelling or clustering

Incentivized

Organizing the data sets is easy and logical. Slicing and dicing of data functionality can be easily performed and is intuitive. Possibility to perform multiple analysis with a single dataset. Data can be easily adjusted even for a non-technical person. Easy navigation. Adjusting of datasets is very intuitive and quickly.

Incentivized

• The ability to conduct a co-browse session quickly and easily has been a big hit for our customers and employee base.
• SaleMove is always looking for creative new ideas to help provide additional value to our customers.

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

• Topic generation
• Customizing process flows
• Slice & dice data

Incentivized

• Lack of SMS integration.
• The development required for integration into custom CRMs.
• Roadmap features AI-powered initiatives, but it is a product that integrates with AI and not a new or advanced AI tool.

• 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

• User interface
• Text analytics
• Segmentation setup

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.

This is Glia's largest strength. The integration and initial configuration were done exclusively by Glia, freeing up our limited technology resources. Especially at the beginning of our relationship, the customer success team on a scheduled basis assisted in the review of our data and KPIs while offering strategies to improve services and achieve higher ROI. None of these services were offered for a premium and this demonstrates the commitment Glia has to launch successful partnerships.

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.

The customer success team was superior, as was the possibility of pro-active engagements across all mediums and platforms. Pricing models in this space are comparable, however, the enhanced auxiliary features, as well as a stronger product road map for development, tipped the scales towards Glia. The product road map is always made available to customers, and most initiatives are deployed on time.

Power BI is stronger for quick ad-hoc analysis and dashboards, but IBM Cognos Analytics is better when consistency, precision, and mass distribution matter. Tableau is best for interactive analysis, while IBM Cognos Analytics is better for standardized, repeatable enterprise reporting. Sigma shines for customizable dashboards and drill-down analysis while IBM Cognos Analytics holds an edge in data discovery and visualization.

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 seen NPS results increase since using SaleMove

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

• Multiple analysis
• Slice & dice of data
• Customizing data models

Incentivized