After beating 2 human Jeopardy game champions three times in a row in 2011 IBM’s Watson has been hard pressed to come up with a comparable winning streak. Initially IBM appeared to expect its largest customers to buy richly configured Power Servers to run Watson on prem. When they didn’t get enough takers the company moved Watson to the cloud where companies could lease it for major knowledge-driven projects. When that didn’t catch on IBM started to lease Watson’s capabilities by the drink, promising to solve problems in onesies and twosies.
Jeopardy champs lose to Watson
Today Watson is promising to speed AI success through IBM’s Watson Knowledge Catalog. As IBM puts it: IBM Watson Knowledge Catalog powers intelligent, self-service discovery of data, models, and more; activating them for artificial intelligence, machine learning, and deep learning. Access, curate, categorize and share data, knowledge assets, and their relationships, wherever they reside.
DancingDinosaur has no doubt that Watson is stunning technology and has been rooting for its success since that first Jeopardy round seven years ago. Over that time, Watson and IBM have become a case study in how not to price, package, and market powerful yet expensive technology. The Watson Knowledge Catalog is yet another pricing and packaging experiment.
Based on the latest information online, Watson Knowledge Catalog is priced according to number of provisioned catalogs and discovery connections. There are two plans available: Lite and Professional. The Lite plan allows 1 catalog and 5 free discovery connections while the Professional plan provides unlimited of both. Huh? This statement begs for clarification and there probably is a lot of information and fine print required to answer the numerous questions the above description raises, but life is too short for DancingDinosaur to rummage around on the Watson Knowledge Catalog site to look for answers. Doesn’t this seem like something Watson itself should be able to clarify with a single click?
But no, that is too easy. Instead IBM takes the high road, which DancingDinosaur calls the education track. Notes Jay Limburn, Senior Technical Staff Member and IBM Offering Manager: there are two main challenges that might impede you from realizing the true value of your data and slowing your journey to adopting artificial intelligence (AI). They are 1) inefficient data management and 2) finding the right tools for all data users.
Actually, the issues start even earlier. In attempting AI most established organizations start at a disadvantage, notes IBM. For example:
- Most enterprises do not know what and where their data is
- Data science and compliance teams are handicapped by the lack of data accessibility
- Enterprises with legacy data are even more handicapped than digitally savvy startups
- AI projects will expose problems with limited data and poor quality; many will simply fail just due to that.
- The need to differentiate through monetization increases in importance with AI
These are not new. People have been whining about this since the most rudimentary data mining attempts were made decades ago. If there is a surprise it is that they have not been resolved by now.
Or maybe they finally have with the IBM Watson Knowledge Catalog. As IBM puts it, the company will deliver what promises to be the ultimate data Catalog that actually illuminates data:
- Knows what data your enterprise has
- Where it resides
- Where it came from
- What it means
- Provide quick access to it
- Ensure protection of use
- Exploit Machine Learning for intelligence and automation
- Enable data scientists, data engineers, stewards and business analysts
- Embeddable everywhere for free, with premium features available in paid editions
OK, after 7 years Watson may be poised to deliver and it has little to do with Jeopardy but with a rapidly growing data catalog market. According to a Research and Markets report, the data catalog market is expected to grow from $210 million in 2017 to $620 million by 2022. How many sales of the Professional version gets IBM a leading share.
DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Follow DancingDinosaur on Twitter, @mainframeblog. See more of his work at technologywriter.com and here.
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