Denodo is the eponymous data integration platform from the global company headquartered in Silicon Valley.
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IBM Planning Analytics
Score 8.3 out of 10
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IBM Planning Analytics, powered by IBM TM1®, is an integrated planning solution designed to promote collaboration across the organization and help keep pace with the speed of modern business. With its calculation engine, this enterprise performance management solution is designed to help users move beyond the limits of spreadsheets, automating the planning process to drive faster, more accurate results. Use it to unify data sources into one single repository, enabling users to build…
Denodo allows us to create and combine new views to create a virtual repository and APIs without a single line of code. It is excellent because it can present connectors with a view format for downstream consumers by flattening a JSON file. Reading or connecting to various sources and displaying a tabular view is an excellent feature. The product's technical data catalog is well-organized.
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.
Caching - but I am sure it will be improved by now. There were times when we expected the cache to be refreshed but it was stale.
Schema generation of endpoints from API response was sometimes incomplete as not all API calls returned all the fields. Will be good to have an ability to load the schema itself (XSD/JSON/Soap XML etc).
Denodo exposed web services were in preliminary stage when we used; I'm sure it will be improved by now.
Export/Import deployment, while it was helpful, there were unexpected issues without any errors during deployment. Issues were only identified during testing. Some views were not created properly and did not work. If it was working in the environment from where it was exported from, it should work in the environment where it is imported.
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
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.
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.
Denodo is a tool to rapidly mash data sources together and create meaningful datasets. It does have its downfalls though. When you create larger, more complex datasets, you will most likely need to cache your datasets, regardless of how proper your joins are set up. Since DV takes data from multiple environments, you are taxing the corporate network, so you need to be conscious of how much data you are sending through the network and truly understand how and when to join datasets due to this.
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
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.
