Last month, IBM made available the beta version of its Watson Analytics data analysis service, an offering first announced in September. It’s one of IBM’s only recent forays into anything resembling consumer software, and it’s supposed to make it easy for anyone to analyze data, relying on natural language processing (thus the Watson branding) to drive the query experience.
When the servers running Watson Analytics are working, it actually delivers on that goal.
Analytic power to the people
Because I was impressed that IBM decided to a cloud service using the freemium business model — and carrying the Watson branding, no less — I wanted to see firsthand how well Watson Analytics works. So I uploaded a CSV file including data from Crunchbase on all companies categorized as “big data,” and I got to work.
Seems like a good starting point.
Choose one and get results. The little icon in the bottom left corner makes it easy to change chart type. Notice the various insights included in the bar at the top. Some are more useful than others.
But which companies have raised the most money? Cloudera by a long shot.
I know Cloudera had a huge investment round in 2014. I wonder how that skews the results for 2014, so I filter it out.
And, voila! For what it’s worth, Cloudera also skews funding totals however you sort them — by year founded, city, month of funding, you name it.
Watson analytics also includes tools for building dashboards and for predictive analysis. The latter could be particularly useful, although that might depend on the dataset. I analyzed Crunchbase data to try and determine what factors are most predictive of a company’s operating status (whether it has shut down, has been acquired or is still running), and the results were pretty obvious (if you can’t read the image, it lists “last funding” as a big predictor).
If I have one big complaint about Watson Analytics, it’s that it’s still a bit buggy — the tool to download charts as images doesn’t seem to work, for example, and I had to reload multiple pages because of server errors. I’d be pretty upset if I were using the paid version, which allows for more storage and larger files, and experienced the same issues. Adding variables to a view without starting over could be easier, too.
Regarding the cloud connection, I rather like what Tableau did with its public version by pairing a locally hosted application with cloud-based storage. If you’re not going to ensure a consistent backend, it seems better to guarantee some level of performance by relying on the user’s machine.
All in all, though, Watson Analytics seems like a good start to a mass-market analytics service. The natural language aspect makes it at least as intuitive as other services I’ve used (a list that includes DataHero, Tableau Public and Google Fusion tables, among others) and it’s easy enough to run and visualize simple analyses. But Watson Analytics plays in a crowded space that includes the aforementioned products, as well as Microsoft Excel and PowerBI, and Salesforce Wave.
If IBM can work out some of the kinks and add some more business-friendly features — such as the upcoming abilities to refine datasets and connect to data sources — it could be onto something. Depending on how demand for mass-market analytics tools shapes up, there could be plenty of business to go around for everyone, or a couple companies that master the user experience could own the space.
Source : Hands on with Watson Analytics: Pretty useful when it’s working, Derrick Harris ( https://gigaom.com/2015/01/18/hands-on-with-watson-analytics-pretty-useful-when-its-working/ )