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…
$825
per month 5 users
Tableau Desktop
Score 8.3 out of 10
N/A
Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
IBM Planning Analytics with Watson is much more flexible and scalable in comparison. IBM PAW is the clear winner for our organization's successful planning and analysis needs.
IBM Planning Analytics was by far the most robust tool we evaluated among several top competitors. It stood out for its place in the industry to provide detailed, integrated, and aggregate integration for data governance. I was impressed with the approach from the sales team to …
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.
Tableau Desktop is one the finest tool available in the market with such a wide range of capabilities in its suite that makes it easy to generate insights. Further, if optimally designed, then its reports are fairly simple to understand, yet capable enough to make changes at the required levels. One can create a variety of visualizations as required by the business or the clients. The data pipelines in the backend are very robust. The tableau desktop also provides options to develop the reports in developer mode, which is one of the finest features to embed and execute even the most complex possible logic. It's easier to operate, simple to navigate, and fluent to understand by the users.
An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.
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.
Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.
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.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
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
I have never really used support much, to be honest. I think the support is not as user-friendly to search and use it. I did have an encounter with them once and it required a bit of going back and forth for licensing before reaching a resolution. They did solve my issue though
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
The training for new users are quite good because it covers topic wise training and the best part was that it also had video tutorials which are very helpful
Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.
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.
If we do not have legacy tools which have already been set up, I would switch the visualization method to open source software via PyCharm, Atom, and Visual Studio IDE. These IDEs cannot directly help you to visualize the data but you can use many python packages to do so through these IDEs.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
Tableau was acquired years ago, and has provided good value with the content created.
Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.
