Most Helpful Review
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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.
It reduces time to reproduce reports, provides easy access to organisational data, and has the ability to generate a wide range of reports and analysis.
It is a central source of up-to-date data and information.
It is able to create information dashboards for various users' throughout.
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.
It needs more presentation/charting capabilities and integration with GIS.
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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.
|Yellowfin offers a business intelligence (BI) platform that allows users to interact with big data in a variety of ways. Yellowfin works to provide big data access to companies of all sizes, from small business to billion-dollar enterprises. It is designed for providing data quickly and allowing users to filter for specific results, maximizing gain from big data. Yellowfin has a variety of dashboards so the user can filter, drill to detail, and have data analysis in the same browser. The data can also be easily shared with others via email, wiki embed, and reports. There is a mobile app as well, which works automatically with the desktop dashboards to allow users to access their data on the go, and alerts can be set up to notify a user via email or push to a mobile device if the data is indicating a critical event taking place. Yellowfin also can map data to locations, providing not only the what of data, but also the where. Lancashire Care NHS Foundation Trust provides its community in England with mental health and community care services. Using Yellowfin's mobile business intelligence capabilities to deliver reporting and analytics to approximately 6000 clinicians, Lancashire Care NHS Foundation Trust was able to greatly improve the quality of its patient care. Yellowfin allowed the Trust to access and share independent data from mobile devices as well as create a Balanced Scoreboard to quickly gather and report information on the company's performance to its executives, management, and directors.|
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|RIMAC, Westpac New Zealand, Toyota Financial Services, Swiss Re, Akershus University Hospital, Korean Air Lines, Mizuho Bank, Honda||NCS, Universitat Konstanz, AT&T, PG&E, SingTel, InternetStores|
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