IBM Watson Explorer vs Teradata Analytics [EOL] comparison

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103 views|79 comparisons
100% willing to recommend
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50% willing to recommend
Executive Summary

We performed a comparison between IBM Watson Explorer and Teradata Analytics [EOL] based on real PeerSpot user reviews.

Find out in this report how the two Data Mining solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed IBM Watson Explorer vs. Teradata Analytics [EOL] Report (Updated: March 2020).
768,924 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"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.""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.""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.""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.""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 valuable feature of Watson Explorer for us is data entities, and to see the hidden insights from within unstructured data."

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"nPath has made journey/path analysis much easier.""It has been fantastic for running complete data sets (no sampling required).""Provides ease of formulating a solution based on SQL-like queries."

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Cons
"It needs better language support, to include some other languages. Also, they should improve the user interface.""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""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""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.""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.""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.""The solution is expensive."

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"I have found some problems with the figures depicted on graphs and figures shown, like scores which could not be negative but which were depicted as such.""I would like to see more/better documentation. They also need to enhance analytic/data science algorithms.""We have struggled with uptime. Some of the features need to be updated."

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Pricing and Cost Advice
Information Not Available
Ranking
9th
out of 18 in Data Mining
Views
103
Comparisons
79
Reviews
0
Average Words per Review
0
Rating
N/A
Unranked
In Data Mining
Buyer's Guide
IBM Watson Explorer vs. Teradata Analytics [EOL]
March 2020
Find out what your peers are saying about IBM Watson Explorer vs. Teradata Analytics [EOL] and other solutions. Updated: March 2020.
768,924 professionals have used our research since 2012.
Comparisons
Also Known As
IBM WEX
Teradata Aster Analytics, Aster Analytics
Learn More
Overview

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.

Teradata Aster® Analytics Portfolio provides a suite of ready-to-use, multi-genre advanced analytics functions that empowers business users to uncover and operationalize non-intuitive insights. Teradata Aster Analytics includes the Aster Database, Aster Client and the Aster Portfolio that consists of SQL, SQL-MapReduce and Graph functions for multi-genre advanced analytics. These functions provide everything from data acquisition and preparation to analytic modeling and visualization.

Sample Customers
RIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, Honda
Information Not Available
Top Industries
VISITORS READING REVIEWS
Computer Software Company19%
Government9%
Financial Services Firm8%
Outsourcing Company8%
No Data Available
Company Size
REVIEWERS
Small Business18%
Midsize Enterprise18%
Large Enterprise64%
VISITORS READING REVIEWS
Small Business24%
Midsize Enterprise10%
Large Enterprise65%
No Data Available
Buyer's Guide
IBM Watson Explorer vs. Teradata Analytics [EOL]
March 2020
Find out what your peers are saying about IBM Watson Explorer vs. Teradata Analytics [EOL] and other solutions. Updated: March 2020.
768,924 professionals have used our research since 2012.

IBM Watson Explorer is ranked 9th in Data Mining while Teradata Analytics [EOL] doesn't meet the minimum requirements to be ranked in Data Mining. IBM Watson Explorer is rated 8.4, while Teradata Analytics [EOL] is rated 7.0. The top reviewer of IBM Watson Explorer writes "Ingests, retrieves information from a range of sources; enables dissecting questions in context and answering them". On the other hand, the top reviewer of Teradata Analytics [EOL] writes "Streamlines formulating solutions based on SQL-like queries". IBM Watson Explorer is most compared with Salesforce Einstein Analytics, Microsoft Power BI and Tableau, whereas Teradata Analytics [EOL] is most compared with . See our IBM Watson Explorer vs. Teradata Analytics [EOL] report.

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.