Overall Satisfaction with IBM Watson Content Analytics
IBM Watson Content Analytics is mostly used for the analytics side of the operation. We use it to analyze text data and other unstructured data. It is also used with structured data. It is only used by a few individuals within the organization with a more advanced understanding of advanced analytics.
- IBM Watson Content Analytics is perfect for individuals wanting a point-and-click user interface that can accomplish a host of advanced data mining tasks.
- Content Analytics works quite well with unstructured data.
- Converting unstructured data to structured data is much easier with Content Analytics than other, competing open source products.
- Content Analytics is competing with open source software that comes with a price tag of $0, but is costly from a human-time perspective. Although human-time is valued, it's hard to see it.
- Because Content Analytics is so good at making the user interface easy, it's sometimes more difficult to do more custom analysis.
- Content Analytics does not run as quickly as other companies' analytics solutions.
- Content Analytics has been a positive ROI in that it made analysts more productive.
- Content Analytics has been a negative ROI in some cases because it has a much smaller user base than other open source products. This smaller user base makes it more difficult to accomplish certain tasks.
- Content Analytics has made text analytics more than delightful. I love it.
- Microsoft Cognitive Toolkit (CNTK), Sisense, Looker, SAP BusinessObjects Business Intelligence (BI) Platform, Alteryx Analytics and Yellowfin
Perhaps the biggest advantage of IBM Watson Content Analytics is the IBM feel. I think IBM puts lots of resources into developing products that even sociologists can use. It's so easy, that to professionals wanting customized analysis, it might be kind of offensive. The drawback is that Content Analytics is not as fast as its competitors.