Dataiku is a French startup and its product, DSS, is a challenger to market incumbents and features some visual tools to assist in building workflows.
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IBM SPSS Statistics
Score 8.5 out of 10
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SPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).
Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
SPSS is well-suited for the following: 1) User Behavior Analysis: SPSS handles large datasets to analyze user behavior data. 2) Customer Satisfaction / Foundational Surveys: SPSS facilitates analysis of quant data from satisfaction surveys, keeping us informed about customer needs and preferences. 3) A/B test analysis: SPSS statistical tools for A/B test analysis, which helps optimize user experience of our products. Scenarios where SPSS are less appropriate: 1) Qualitative Data Analysis: I do not use SPSS for open-ended survey responses/qual data. 2) Live/in-vivo data analysis: SPSS is not ideal for real-time data processing. 3) Complex Data Integration: SPSS isn’t the best fit for complex data integration tasks
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.
It would be beneficial to have AMOS as part of the SPSS package instead of purchasing it separately.
It would be beneficial to have other statistical tests, such as PROCESS, be part of the standard SPSS tests instead of having the need to run a syntax to have it installed.
My dataset tends to be smaller, and I have never had any issues with using SPSS. I heard that SPSS may not be optimal when handling large datasets.
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
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
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.
The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
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
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.
Strictly for Data Science operations, Anaconda can be considered as a subset of Dataiku DSS. While Anaconda supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
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.
