Most Helpful Review
Find out what your peers are saying about IBM Watson Explorer vs. SAS Analytics and other solutions. Updated: November 2019.
378,950 professionals have used our research since 2012.
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
The valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data.
We take natural language that was happening in our repositories and our application and then feed it to the Watson APIs. We receive JSON payloads as an API response to get cognitive feedback from the repository data.
Ease of use is pretty good as is the standardization of not actually having to have my own natural learning algorithms, just to use the Watson APIs.
For me, as a user, the most valuable feature is the ability to ingest and then retrieve information from a range of separate sources; the ability to dissect questions in context and actually answer them.
The ability to easily pull together lots of different pieces of information and drill down in a smarter way than has been possible with other analytics tools is key. Watson is all based on a set of AI and deep learning, machine-learning capabilities, and it is looking behind the scenes at some relationships that you likely would not have spotted on your own. It's pulling things together, categorizing some things, that are not something that you might have seen on your own.
The most valuable feature is the ability to handle large data sets.
Modeling ones and figures, such as PROC LIFETEST, PROC LOGISTICS, PROC GPLOT. PROC FREQ and PROC MEANS, are also among the valuable features.
It has facilitated timely analysis results with quality work and meaningful output.
I use it to replicate our entire financial system to verify/duplicate calculations.
I use SAS daily to analyze data, produce reports, and other outputs.
SAS Business Intelligence is well-suited for our large corporation. We have demand for scalable and reliable insights into information which is housed in our large systems.
It is able to connect to all major platforms, and all the smaller platforms that I have come across.
It has also been around for an extremely long time, has a strong history, and good market penetration.
It is a little bit tricky to get used to the workflow of knowing how to train Watson, what can be provided, what can't be, how to provide it, how to import, export, and what it means every time you have to add a new dictionary
It needs better language support, to include some other languages. Also, they should improve the user interface.
I would say, give some kind of a community edition, a free edition. A lot of companies do, even Amazon gives you some kind of trial and error opportunities. If they could provide something like that, it would be good.
Stability is actually one of the areas that could use improvement. Setting it up is always tough. Setting Explorer requires experts, but also the underlying platform is not that stable. So it really needs a good expert to keep it running.
More cognitive feedback would be good. The natural language analysis is great, the sentiment analyzers are great. But I would just like to see more... innovation done with the Watson platform.
Much of IBM operates this way, where they have sets of tools that are in the middleware space, and it becomes the customer's responsibility or the business partner's responsibility to develop full solutions that take advantage of that middleware. I think IBM's finding itself in that spot with Watson-related technologies as well, where the capabilities to do really interesting and useful things for customers is there, but somebody still has to build it. Is that going to be the customer? Are they going to be willing to take on that responsibility themselves
Small businesses will probably have a little harder time getting into it, just because of the amount of resources that they have available, both financial and time, but it really is a solution that should work for them.
This solution should be made more user-friendly.
Once a SAS figure is produced one would like to modify things, such as titles, legends, and incorporate risk sets as a footer on the plots.
Support at universities used to be limited, but I hear this is changing.
The training for SAS Business Intelligence is often difficult to arrange. It is often cancelled due to not enough people being enrolled.
I would like to see their interface to R added to either Base SAS or SAS Analytics.
Pricing and Cost Advice
Information Not Available
The cost for SAS Business Intelligence can prove to be a little prohibitive.
Setup costs were quite reasonable.
Prices were comparable with alternative solutions.
Licensing was rather straightforward.
It is relatively expensive. It is not an easy software to afford.
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
IBM Watson Explorer is a cognitive exploration and content analysis platform that lets you listen to your data for advice. Explore and analyze structured, unstructured, internal, external and public content to uncover trends and patterns that improve decision-making, customer service and ROI. Leverage built-in cognitive capabilities powered by machine learning models, natural language processing and next-generation APIs to unlock hidden value in all your data. Gain a secure 360-degree view of customers, in context, to deliver better experiences for your clients.
|SAS was founded in 1976 and actually began as a project at North Carolina State University to analyze agriculture research. It has since become a global company that is recognized for its innovation in data analytics and business intelligence. SAS is redefining what's possible with data analytics through greater efficiency, strong information value chains, effective collaboration tools, and state-of-the-art visualization software. SAS Analytics is designed for use in a variety of industries including government, manufacturing, higher education, defense & security, banking, automotive, communications, and much more. SAS Analytics is a business intelligence (BI) solution that has the ability to reveal patterns and anomalies in data, identify relationships and different variables, and predict future outcomes. Users of SAS Analytics will benefit from making more sound, better informed business decisions based on company data and market trends. Data mining, data visualization, text analytics, forecasting, statistical analysis, and more are all available through SAS Analytics. Staples, which boasts $27 billion in sales across the globe, has a business philosophy that prioritizes customer loyalty and satisfaction. In order to better engage their customers, Staples utilizes SAS Analytics to plan finely tuned marketing campaigns. Through forecasting and advanced analytics, Staples has been able to rely on fewer contractors, and cut their marketing budget, while improving their customer retention rate.|
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