IBM SPSS Statistics vs. SAP Predictive Analytics

I described earlier that the only scenarios where I use SPSS are those where we have legacy projects that were developed in the late 90s or early 2000s using SPSS, and for some reason, the project (data set, scope, etc.) hasn't changed in 24+ years. This counts for 1-2 out of around 80 projects that I run. Whenever possible, I actively have my team move away from SPSS, even when that process is painful.

Incentivized

It's a great tool to merge actual data analysis (which Lumira doesn't do that well) with visualization (which Lumira does well) - so it can be seen as Lumira for data analysts. However, a lot of the 'predictive' side is hidden/black box which can be frustrating for those analysts, so you could argue it is too complex for casual users, but too 'black box' for analysts.

Incentivized

• SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
• Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
• SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
• SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
• In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.

Incentivized

• It doesn't require you to have a Ph.D. to build models!
• You can use it to address a very large and wide dataset without worrying about sampling.
• Automation is in the product DNA. You can prepare your data, ingest it into the "Kernel", then get insights about what was found, decide to publish it and schedule scoring tasks or model refresh in the same product.

Incentivized

• collaboration - SPSS lacks collaboration features which makes it near impossible to collaborate with my team on analysis. We have to send files back and forth, which is tedious.
• integration - I wish SPSS had integration capabilities with some of the other tools that I use (e.g., Airtable, Figma, etc.)
• user interface - this could definitely be modernized. In my experience, the UI is clunky and feels dated, which can negatively impact my experience using the tool.

Incentivized

• Working with this software is very simple and enjoyable for me as [an] IT consultant and expert, but it is a bit complicated for novice users.
• Some big data takes more time‌to load, which I think could be faster

Incentivized

Both
money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis
using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data
entry and data analysis for my research. Output from SPSS is very easy to
interpret for data analysis and findings

Incentivized

Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.

Incentivized

the UI is a bit dated and available as a desktop tool mostly.

Incentivized

SPSS can tend to crash when I am trying to do a lot of data. This can slow me down when I need to do a lot of data

Incentivized

SPSS does the job, but it can be slow. I do have to plan a lot of time to get through a huge amount of data.

Incentivized

I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end

The documentation provides an explanation about what features are available but not necessarily what's happening behind the scenes. On the other side, the "community" has grown since the acquisition and most questions are properly addressed by SAP folks. Since the "product maintenance" mode announcement was made, there wasn't much new content published except on the Smart Predict side (which is built by the SAP Predictive Analytics team)

Incentivized

Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.

Incentivized

I have used R when I didn't have access to SPSS. It takes me longer because I'm terrible at syntax but it is powerful and it can be enjoyable to only have to wrestle with syntax and not a difficult UI.

Incentivized

We have typically used Spotfire for data analysis but decided to move to SAP Business Objects due to its innate connection with SAP. I found Lumira to be good for visualizations but it is not meant for data analysis. Therefore, we have introduced Predictive Analytics to see if it can fill that gap. So far, it's been far less intuitive than Spotfire to get started, and as far as I am aware so far, it does not bring many additional capabilities. I do, however, like that it utilizes the Lumira look/feel and integrates very well.

Incentivized

I am neutral because I have not had to look into scalability since I am using as a student.

Incentivized

• I found SPSS easier to use than SAS as it's more intuitive to me.
• The learning curve to use SPSS is less compared to SAS.
• I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.

Incentivized

• Proper forecasting increases our credibility with partners and customers
• Forecasting determines the amount of investment in each sector and reduces the cost of additional costs

Incentivized