Compare IBM Watson Explorer vs. KNIME

IBM Watson Explorer is ranked 3rd in Data Mining with 9 reviews while KNIME is ranked 1st in Data Mining with 10 reviews. IBM Watson Explorer is rated 8.2, while KNIME is rated 8.4. The top reviewer of IBM Watson Explorer writes "Facilitates utilizing data streams that we haven't tapped into, and producing results that are tremendously useful, company-wide". On the other hand, the top reviewer of KNIME writes "Our average record size was around 10 million records. If we have bigger data, we can opt for a Big Data extension for Hadoop, Spark, etc". IBM Watson Explorer is most compared with SAS Analytics, IBM SPSS Modeler and IBM Cognos, whereas KNIME is most compared with Alteryx, RapidMiner and Weka. See our IBM Watson Explorer vs. KNIME report.
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IBM Watson Explorer Logo
1,346 views|657 comparisons
KNIME Logo
Read 10 KNIME reviews.
21,168 views|16,525 comparisons
Most Helpful Review
Find out what your peers are saying about IBM Watson Explorer vs. KNIME and other solutions. Updated: November 2019.
378,570 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
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.

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This solution is easy to use and especially good at data preparation and wrapping.It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop.Key features include: very easy-to-use visual interface; Help functions and clear explanations of the functionalities and the used algorithms; Data Wrangling and data manipulation functionalities are certainly sufficient, as well as the looping possibilities which help you to automate parts of the analysis.Clear view of the data at every step of ETL process enables changing the flow as needed.We leverage KNIME flexibility in order to query data from our database and manipulate them for any ad-hoc business case, before presenting results to stakeholders.The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine.Easy to connect with every database: We use queries from SQL, Redshift, Oracle.We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics.

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Cons
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 dictionaryIt 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 themselvesSmall 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.

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It needs more examples, use cases, and MOOC to learn, especially with respect to the algorithms and how to practically create a flow from end-to-end.They could add more detailed examples of the functionality of every node, how it works and how we can use it, to make things easier at the beginning.The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R).The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily.‚ÄčThe data visualization part is the area most in need of improvement.The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best.Data visualization needs improvement.I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something.

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Pricing and Cost Advice
Information Not Available
KNIME desktop is free, which is great for analytics teams. Server is well priced, depending on how much support is required.

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378,570 professionals have used our research since 2012.
Ranking
3rd
out of 16 in Data Mining
Views
1,346
Comparisons
657
Reviews
9
Average Words per Review
476
Avg. Rating
8.1
1st
out of 16 in Data Mining
Views
21,168
Comparisons
16,525
Reviews
10
Average Words per Review
333
Avg. Rating
8.4
Top Comparisons
Compared 25% of the time.
Compared 15% of the time.
Compared 41% of the time.
Compared 14% of the time.
Compared 7% of the time.
Also Known As
IBM WEXKNIME Analytics Platform
Learn
IBM
Knime
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.

KNIME is the leading open platform for data-driven innovation helping organizations to stay ahead of change. Use our open-source, enterprise-grade analytics platform to discover the potential hidden in your data, mine for fresh insights or predict new futures.
Offer
Learn more about IBM Watson Explorer
Learn more about KNIME
Sample Customers
RIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, HondaInfocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Top Industries
No Data Available
VISITORS READING REVIEWS
Software R&D Company24%
Comms Service Provider16%
Manufacturing Company9%
Financial Services Firm8%
Company Size
REVIEWERS
Small Business20%
Midsize Enterprise20%
Large Enterprise60%
REVIEWERS
Small Business27%
Midsize Enterprise27%
Large Enterprise45%
VISITORS READING REVIEWS
Small Business17%
Midsize Enterprise2%
Large Enterprise82%
Find out what your peers are saying about IBM Watson Explorer vs. KNIME and other solutions. Updated: November 2019.
378,570 professionals have used our research since 2012.
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.
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