Last up an executive panel focused on Watson Analytics:
How much data, how complex or what kind of data drives value from Watson Analytics?
- Self-service is core to the value proposition more than the kind of data or volume of data
- If you have only a little data then one of the interesting aspects is the ability to find external data that might augment it effectively
What is IBM doing to enable partners to work with this new kind of technology/new approach?
- Lots of investment in tooling such as a content store and tools to let people add and analyze their own content
- See a growth in tools to make the process of moving up the Watson learning curve easier like ontologies, shared content etc. This will really change how this kind of technology will be used.
- The freemium model for Watson Analytics is also driven by a desire to see more use cases and so drive more experience with the Watson side of the process in new areas – new kinds of natural language processing for instance.
How do you plan to monetize Watson Analytics?
- Increasing importance of individuals in decision-making when it comes to picking solutions so freemium model is key.
- See the importance of more data sources in analytics so these may be monentizable.
- Collaboration, security and other enterprise features will also likely drive monetization.
- May also be degrees of analytic sophistication in for-fee versions as well as access to a partner ecosystem
- The free version will not be 100% of the product but will be designed to give them lots of opportunity while still creating demand for the premium product.
How does Watson Analytics bring IT and the BI competency center, for instance, into the conversation?
- Data access and trust is going to be key, with the BI / IT team working to provide this data through the Data Refinery infrastructure
- The scalability of all this will also help these teams reach more of the problems out there and scale the experts they already have.
And that’s a wrap.