IBM InfoSphere Information Server vs. IBM Planning Analytics

Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.

Ideal for large organization with complex multi-dimensional data, large budgets and dedicated administrator support. The performance of the TM1 data base is unmatched. The PAW and PAX options providing planners to work in both Excel and workspace environment. Higher Implementation efforts due to the greenfield implementations. Visualization features are not up to the mark.

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• IIS best for ETL ,not ELT , and many and diffrent source systems.
• It also can process big data , unstuctured data
• It is not only DWH , you can use infosphere for analys and see the bigger architecture of your OLTP systems

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• Handle very large data volumes.
• Scale to a large number of users.
• Not having to compromise on business complexity.
• It can be run by business users.
• Availability of highly qualified consultants to support businesses.
• REST API allows for an open eco system and a variety of solutions to extend the product.
• Vast integration possibilities.
• AI-infused engine with IBM Watson.

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• I would be nice to have a new web development environment for DataStage.
• Connectivity Packs such as Pack for SAP Application are a little pricey.
• It is confusing for new developers the possibility of developing jobs using different execution engines such as Parallel or Server.

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• sometimes it is hard to produce pixel perfect reports from the Web UI. I know it is not made for this, but still, it'll be great
• getting in e.g. an Excel file just by drag and drop, and the AI should "understand" what the data is all around

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• Scale of implementation
• IBM techsupport

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Since IBM Cognos Express is suitable only for medium data warehouse environment, we are not sure if this tool solves the long term need as the business keeps growing rapidly. So its a 50/50 ratio to renew Express license. But having said that, the components of IBM Cognos Express are also available in other Cognos BI suites like Cognos 10.x version. So we will probably upgrade our environment to IBM Cognos 10.x which comes with more new features.

IBM Planning Analytics is generally good in terms of functionalities. It can be used reduce time for budget planning, resource planning, demand forecasting, etc. The performance of IBM Planning Analytics is acceptable, but user interface can be improved. It would be good to see new features that allow users to customise the dashboard.

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IBM support has been very quick to respond and handle the very few issues we've had. We've had a third-party who partners with IBM to be our consulting team which has helped greatly reduce the need for us to contact IBM directly. I highly recommend researching and selecting a well-respected partner to help with an implementation as well as ongoing support as needed.

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DataStage is more robust and stable than ODI The ability to perform complex transformations or implement business rules is much more developed in DS

For strong technical teams and flexibility IBM Planning Analytics is the way to go. For quicker adoption and less technical teams Anaplan is the best option. If consolidation, financials, and moving from legacy tools are main focus than OneStream will be a really good choice. If deeply invested into SAP already than the SAP BPC will be the best fit to maintain the investment.

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• Productivity of the development of integration processes.
• Better documentation and governance.
• Reduce training costs of various technologies.

• Automate direct data connections to multiple data sources
• One secured version of the the truth (for data and formulas)
• Ability to scale to much more detailed planning with option to create predictive forecasts at detail
• Business user friendly with powerful Excel integration
• Very flexible and powerful modeling, can handle custom modeling needs at scale
• Can make the same data available across finance and ops, but at the level of details and timeline that makes sense for them

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