We performed a comparison between Google Data Studio and IBM Watson Explorer based on real PeerSpot user reviews.
Find out in this report how the two Reporting solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The ability to design complex data models and equations."
"This has improved our organization by allowing people to see their data and develop visualizations themselves."
"Valuable features include advanced integrated analysis and easy implementation."
"I am impressed with the tool's scheduling mechanism, refresh mechanism, and different types of charts."
"The solution is free so that is a good feature."
"The ability to integrate with a great variety of data sources."
"Data Studio integrates seamlessly with other Google products, and we can use it with other APIs if we like."
"I find it favorable regarding speed of development, ease of building, and flexibility."
"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."
"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."
"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."
"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."
"Panels are not as easy to use as other data extraction UIs."
"There is a significant degree of sophistication required to compete with Tableau or Cognos."
"Stability and scalability an be improved for a full ten."
"Insisting on forums, blogs and community outreach in communications, and posting videos on an established calendar would be useful."
"It's not yet a replacement for a complete BI tool."
"There are issues with integration and I encountered limits and warnings, especially with my pivot table size."
"When you physically install a product on one machine instead of the cloud, you have a better visibility, best icon quality, etc.. It's more of an issue with how we are adapting to the transition. We are still in the early moments of using this tool, and we need to go deeper to discover some improvements."
"The tool should come up with data modeling layer features that are present in other products like Power BI."
"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."
"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"
"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."
"It needs better language support, to include some other languages. Also, they should improve the user interface."
"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."
"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."
"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"
Earn 20 points
Google Data Studio is ranked 14th in Reporting with 7 reviews while IBM Watson Explorer is ranked 8th in Data Mining. Google Data Studio is rated 7.8, while IBM Watson Explorer is rated 8.4. The top reviewer of Google Data Studio writes "The cloud environment makes it easier to use large volumes of data and collaborate with coworkers". On the other hand, the top reviewer of IBM Watson Explorer writes "Ingests, retrieves information from a range of sources; enables dissecting questions in context and answering them". Google Data Studio is most compared with Amazon QuickSight, Tableau, Looker, Microsoft Power BI and Databricks, whereas IBM Watson Explorer is most compared with Salesforce Einstein Analytics, Microsoft Power BI, Tableau and KNIME. See our Google Data Studio vs. IBM Watson Explorer report.
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