We performed a comparison between IBM SPSS Modeler and Microsoft Power BI based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly."
"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."
"The supervised models are valuable. It is also very organized and easy to use."
"Some basic form of feature engineering for classification models. This really quickens the model development process."
"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."
"So far, the stability has been rock solid."
"The ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that."
"We have been able to do some predictive modeling with it"
"The initial setup is pretty straightforward."
"The visualization part and its inclusion in a cloud-based application are valuable features."
"Like all Microsoft products, it is very easy to set up initially."
"You don't need much support with Microsoft Power BI because it has such a large base of users who can answer your questions on their forums. There are also many video tutorials and webinars available online that offer solutions to whatever problems you may have."
"In my opinion, Microsoft BI is a low-cost solution, and it could be an interesting solution for a tourism company."
"The way data is presented is very valuable. The amount of information that we can get at a glance is also valuable. You can then drill-down and see data from many different angles in the same chart by selecting certain things. Based on the selection, everything changes automatically. If we have four parameters in a particular item, when you select a parameter, the remaining charts on that page automatically change for that particular parameter."
"In contrast to what we were using before I think that Power BI has given us more extensive results."
"The scalability is good. We have 20 people in my organization using this solution and plan to increase usage."
"I would not rate the technical support very well. The technicians have accents. When you do find someone, it is very hard to get somebody able to answer the technical questions."
"I would like better integration into the Weather Company solution. I have raised a couple of concerns about this integration and having more time series capabilities."
"The standard package (personal) is not supported for database connection."
"I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it."
"The time series should be improved."
"Unstructured data is not appropriate for SPSS Modeler."
"The platform that you can deploy it on needs improvement because I think it is Windows only. I do not think it can run off a Red Hat, like the server products. I am pretty sure it is Windows and AIX only."
"The forecasting could be a bit easier."
"I would like to see better, undisturbed stability without any interruptions."
"I would like to see a more user-friendly interface with Microsoft BI."
"If you need data in real-time, it's not an ideal solution."
"Microsoft BI can improve some of the visual level filters or visual functionality, that are available in other BI tools, such as Tableau or Qlik Sense."
"Microsoft is behind IBM when it comes to security features."
"Microsoft BI comes under pressure when there is a lot of data to be crunched. It gets slower and slower, and the functionality becomes a bit of a problem. The performance goes down with data being fed into the system. The infrastructure requirement also increases if you have to increase the performance. This is the area that can be improved in my opinion. Initially, the product is good, but over the years, when data gets accumulated, it becomes a problem unless the old data is kind of archived and is no longer shown on the visualization. It has a feature by using which a user can query for a report through simple questions to a bot. So, if I want to look for the customer share of revenue by geography, I just simply state that in the chatbot. If I wanted it in a pie chart, then you say, "Please show it to me in a pie chart." It comes out well for basic charts. This feature should be improvised more so that people can very quickly get customized reports on the go."
"One thing I would like to have is the scripting language, as they already have within Excel. It's already within a Microsoft business product, because Excel is the number one business product out there. So it would be nice to have the scripting capability in order to automate certain processes."
"The biggest thing with Microsoft right now is better support. There should be more timely support. We can do 90% of it ourselves by the same token. When we're into the 10%, we do not get timely support via Microsoft's support team."
IBM SPSS Modeler is ranked 4th in Data Mining with 38 reviews while Microsoft Power BI is ranked 1st in BI (Business Intelligence) Tools with 297 reviews. IBM SPSS Modeler is rated 8.0, while Microsoft Power BI is rated 8.0. The top reviewer of IBM SPSS Modeler writes "Easy to use, quick to learn, and offers many ways to analyze data". On the other hand, the top reviewer of Microsoft Power BI writes "A complete ecosystem with an builtin ETL tool, good integrations with python and R, and support of DAX and Power Query (M languages)". IBM SPSS Modeler is most compared with KNIME, IBM SPSS Statistics, RapidMiner, Alteryx and SAS Visual Analytics, whereas Microsoft Power BI is most compared with Tableau, Amazon QuickSight, KNIME, Domo and Oracle OBIEE.
We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
