Most Helpful Review
Researched KNIME but chose IBM SPSS Statistics: Good machine learning algorithms and statistical models, but technical support needs to be more responsive
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
It has the ability to easily change any variable in our research.
They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do.
The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS.
You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use.
The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important.
Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files.
Most of the product features are good but I particularly like the linear regression analysis.
This open-source product can compete with category leaders in ELT software.
This solution is easy to use and especially good at data preparation and wrapping.
It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop.
Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis.
Clear view of the data at every step of ETL process enables changing the flow as needed.
We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders.
The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine.
Easy to connect with every database: We use queries from SQL, Redshift, Oracle.
The design of the experience can be improved.
The product should provide more ways to import data and export results that are user-friendly for high-level executives.
One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated.
Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance.
The statistics should be more self-explanatory with detailed automated reports.
Technical support needs some improvement, as they do not respond as quickly as we would like.
I think the visualization and charting should be changed and made easier and more effective.
The ability to handle large amounts of data and performance in processing need to be improved.
It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end.
They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning.
The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R).
The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily.
The data visualization part is the area most in need of improvement.
The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best.
Data visualization needs improvement.
Pricing and Cost Advice
We think that IBM SPSS is expensive for this function.
KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required.
out of 16 in Data Mining
Average Words per Review
out of 16 in Data Mining
Average Words per Review
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Also Known As
|SPSS Statistics||KNIME Analytics Platform|
|Your organization has more data than ever, but spreadsheets and basic statistical analysis tools limit its usefulness. IBM SPSS Statistics software can help you find new relationships in the data and predict what will likely happen next. Virtually eliminate time-consuming data prep; and quickly create, manipulate and distribute insights for decision making.||KNIME is the leading open platform for data-driven innovation helping organizations to stay ahead of change. Use our open-source, enterprise-grade analytics platform to discover the potential hidden in your data, mine for fresh insights or predict new futures.|
Learn more about IBM SPSS Statistics
Learn more about KNIME
|LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA||Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG|
Financial Services Firm14%
Software R&D Company23%
Comms Service Provider16%
Financial Services Firm9%