Likelihood to Recommend I would be likely to recommend IBM Planning Analytics, particularly in scenarios where comprehensive financial and operational planning is essential. For instance, in our construction company, it is awesome for optimizing resource allocation across multiple projects, creating detailed project budgets, and conducting risk analysis to mitigate project uncertainties.
Read full review It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
Read full review Pros Forecasting after taking into account seasonal trends and exceptional transactions Unlike spreadsheets, there is no fear of an user making changes to the mastercopy accidentally. Each user gets his or her own workspace to analyze. For entities operating in multiple countries, connects seamlessly with IBM Cognos Controller for taking into account variation in currencies Read full review Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc. SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly. Enforced best-practices set up POCs for deployment in production with a minimum of re-work. Estimator validation lets data scientists test and prove different models. Read full review Cons IBM Planning Analytics was an upgrade from an older version of TM1 that is experiencing some growing pains, some functionality is harder to reach than it has been in the past It is easy to learn as a surface user with created reports, but it does require some technical skills to make advanced calculations and reports if there is no reliable consultant available, much like Excel Read full review The cost is steep and so only companies with resources can afford it It will be nice to have Chinese versions so that Chinese engineers can also use it easily It takes a while to learn how to input different kinds of skin defects for detection Read full review Likelihood to Renew 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.
Read full review because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
Read full review Usability For developers, admins and end users looking for flexibility, IBM Planning Analytics would rate very highly on usability. For example, a developer has access to a highly performant built-in ETL (Extract Translate Load) tool and scripting language called Turbo Integrator that can (among other things) bring in data via flat file or direct connection from many data sources, move data around Planning Analytics, perform batch calculations, export to files or other data stores. In the rare situation where limitations are encountered there is a well documented REST API. Admins and end users benefit from the intuitive PAW (Workspace) interface as well as the rich Excel integration through Planning Analytics for Excel (PAfE). Since flexibility inherently comes with a little more complexity, so an organization with simple and "cookie-cutter" requirements may rate Planning Analytics a little lower.
Read full review The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
Read full review Reliability and Availability From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
Read full review Performance Never had slow response even on our very busy network
Read full review Support Rating Although I find the IBM Planning analytics documentation quite time consuming, their support with email and call is something i can term as very considerate and patient, I have had few calls about the features and how i would want to implement them within my projects, and the teams have been super helpful to resolve my issues
Read full review I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
Read full review In-Person Training The trainers on the job are very smart with solutions and very able in teaching
Read full review Online Training The Platform is very handy and suggests further steps according my previous interests
Read full review Implementation Rating It surprised us with unpredictable case of use and brand new points of view
Read full review Alternatives Considered Anaplan does not handle sparsity; this is very problematic for large volume data sets (many 0's). There also are limitations to the number of dimensions that can be used in a module. If more dimensions are required, then separate modules need to be built and intertwined. IBM PA does not have these limitations.
Read full review The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
Read full review Scalability It helped us in getting from 0 to DSX without getting lost
Read full review Return on Investment One of the advantage is on its ability to ease budget and planning Secondly,the fact that it allows for forecasting means based on such insights means that organisations are able to prepare for future eventualities Thirdly, since it can accommodate data from multiple sources means that one is able to carry out best business practices like planning. Read full review Could instantly show data driven insights to drive 20% incremental revenue over existing results Still don't have a real use case for unstructured data like twitter feed Some of the insights around user actions have driven new projects to automate mundane tasks Read full review ScreenShots IBM Planning Analytics Screenshots