Top 8 Data Mining
KNIMEIBM SPSS StatisticsIBM SPSS ModelerWekaSAS AnalyticsOracle Advanced AnalyticsIBM Watson ExplorerSAS Enterprise Miner
Easy to use, stable, and powerful.
We have found KNIME valuable when it comes to its visualization.
The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful.
The most valuable features of the IBM SPSS Modeler are visual programming, you don't have to write any code, and it is easy to use. 90 to 95 percent of the use cases, you don't have to fine-tune anything. If you want to do something deeper, for example, create a better neural network, then you have to go into the features and try to fine-tune them. However, the default selection which is made by the tool, it's very practical and works well.
It doesn’t cost anything to use the product.
There are many options where you can fill all of the data pre-processing options that you can implement when you're importing the data. You can also normalize the data and standardize it in an easier way.
All of the data analytics features in SAS Analytics are valuable to us since we're using them daily across our entire analytics team.
It's very easy to use once you learn it.
When needed, we will work closely with Oracle support and implement their workaround in our application.
The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic.
I have found the auto-generated document very useful as well as the main keywords that are highlighted, which are used for the search functionality within IBM Watson Explorer.
I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks.