Conga Grid vs. IBM Cognos Analytics vs. NodeXL Pro

If a user has to perform a specific update over many records, don't use a List view... use Grid. It allows users to quickly track their work, set additional formatting preferences and avoid constantly tracking work outside of Salesforce which leads data discrepencies and errors.

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

It is suited for social scientists who are more focused on the interpretation that fits in the area of Social Science and Humanity and has nothing to do with computer programming and mathematics

• Allows recruiters to service candidates within a radius of a desired city/location
• Allows recruiters to see multiple fields/information on multiple candidates at once
• Allows for easier ranking/sorting by salary, years of experience, etc

Incentivized

• Data Visualization: Plenty of options exist for multiple use cases, and dashboards are easy to implement and customize.
• Integration with IBM Watson: makes it easy to use Watson AI features (NLP etc.) on your data.
• Its advanced analytics functionalities with powerful pattern detection/prediction models.

Incentivized

• extracting the data from the social media
• visualising the big data of the social media
• sentiment analysis
• cluster analysis
• time series analysis

• Sometimes Conga goes slower when using it at a high volume
• Being able to pull more data through LinkedIn and Indeed
• Job match function

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

• It would be nice if NodeXL can analyse other type of social media such as Instagram, Facebook and TikTok
• It would be nice if it is 100 percent stable, as sometimes I have a problem with error in NodeXL when it is processing the data
• It would be nice if is able to reduce the price for adding Microsoft Power BI in NodeXL

It took my BI team one year to become productive at developing useful content on the IBM Cognos platform. After this year, the reports being developed for a client were stale and no longer relative to the ever changing needs of the business client. Given the same opportunity, I would select a platform that allows the team to quickly produce BI content. Fail fast and recover quickly!

It could be easier to create views or there could be additional training with step by step examples in conga community

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.

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.

In general, Conga is a strong company with a depth of talent in its support team. However, when new releases occur, the changes can be somewhat jarring to users as the interface does not offer the ability to hide or show messages related to the changes - all users get the same messaging from Conga around changes to their tool.

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

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

The implementation was handled very well. The initial implementation exposed a lot of disagreement between our campuses and departments as to how we define data. This was not entirely unexpected, but I thought that we did a nice job as a team to work through some of these challenges.

CongaGrid is native to Salesforce and takes advantage of the Salesforce Lightning experience to provide a strong, full-featured solution for cross-object data access and manipulation. The upgrades are seamless, occurring without requiring administrator application of the changes. Embedding Excel-like functionality directly within Salesforce opens up a host of use cases for accessing and manipulating Salesforce data.

Incentivized

IBM Cognos Analytics is robust in terms of reporting, governance and scheduling while Power BI excels in use, interactivity and visuals. In nutshell, IBM Cognos Analytics has edge over Power BI for enterprise grade , structured reporting needs.

Incentivized

NodeXL is userfriendly, and needed for conducting advanced data analysis techniques which emphasizes the metrics of the visualization NodeXL produce an interesting interactive visualisation

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 has benefited us positively, as I stated earlier- it allows us to filter down results of 65,000+ candidates to a search of 1-100 candidates.

Incentivized

• The platform can be pretty pricey.
• Convoluted contracts and they fine you for any breach during audits.
• Things are changed between releases without any warning and break.
• It is second to none at being able to customize list and crosstab type reports.
• You can easily set up a report to be emailed out every day and even have it export the report to a shared folder.
• On-prem environments can be scaled up pretty much as much as you would like.

Incentivized

• More advance in analysis data
• Attract more people to collaborate with me
• Minimise the time for analysing the data