EzzAbdelfattahAssociate Professor of Statistics at KAU
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Most of the product features are good but I particularly like the linear regression analysis."
"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."
"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."
"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."
"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."
"It has the ability to easily change any variable in our research."
"The most valuable feature is the user interface because you don't need to write code."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"Ability to pull together multiple sources of information."
"The dashboard interface is intuitive and the user is able to interact with it to receive good results from the analytic."
"I think the visualization and charting should be changed and made easier and more effective."
"Technical support needs some improvement, as they do not respond as quickly as we would like."
"The statistics should be more self-explanatory with detailed automated reports."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"The design of the experience can be improved."
"This solution is not suitable for use with Big Data."
"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."
"Could use some refinement getting things that are not standard cloud applications, but more customized."
"There are some transactions we have not been able to find through the dashboard."
"We think that IBM SPSS is expensive for this function."
"The price of this solution is a little bit high, which was a problem for my company."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"The solution is priced well."
Oracle Advanced Analytics 12c delivers parallelized in-database implementations of data mining algorithms and integration with open source R. Data analysts use Oracle Data Miner GUI and R to build and evaluate predictive models and leverage R packages and graphs. Application developers deploy Oracle Advanced Analytics models using SQL data mining functions and R. With the Oracle Advanced Analytics option, Oracle extends the Oracle Database to an sclable analytical platform that mines more data and data types, eliminates data movement, and preserves security to anticipate customer behavior, detect patterns, and deliver actionable insights. Oracle Big Data SQL adds new big data sources and Oracle R Advanced Analytics for Hadoop provides algorithms that run on Hadoop.
IBM SPSS Statistics is ranked 2nd in Data Mining with 15 reviews while Oracle Advanced Analytics is ranked 7th in Data Mining with 2 reviews. IBM SPSS Statistics is rated 8.0, while Oracle Advanced Analytics is rated 9.6. The top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". On the other hand, the top reviewer of Oracle Advanced Analytics writes "Great ability to pull together multiple sources of information, simple for non-technical users ". IBM SPSS Statistics is most compared with IBM SPSS Modeler, TIBCO Statistica, Weka, MathWorks Matlab and Google Cloud Datalab, whereas Oracle Advanced Analytics is most compared with SAS Analytics, OpenText Magellan Text Mining, Weka, IBM SPSS Modeler and KNIME.
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