Data connectors in Watson Analytics is one of the world’s best kept secrets. And, I haven’t helped.
When I write about Watson Analytics, I almost always talk about how easy it is to upload data and get started with your analysis. In my basketball blogs, for example, I download a spreadsheet of team data. Then, I upload it into Watson Analytics and explain how I fill out my brackets. I’ve also described how you can use Datawatch Monarch to prepare structured and semi-structured data before you upload it. And, all that’s great, but it’s time to give data connectors their due.
Uploading isn’t the only way
Thanks to partnerships with some great companies, uploading data is only part of the data access Watson Analytics provides. The other part is in the form of data connectors to familiar sources like EventBrite, HubSpot, SugarCRM, SurveyMonkey and more.
As long as I have the right credentials for these sources, I can connect to them. Then, I can bring that data right into Watson Analytics. I simply click the source’s name, log in and set up my data. After that, I click Import. Watson Analytics adds a data set to my workspace just as if I had uploaded a spreadsheet. And, I’m ready for some starting points.
This is what happened when I selected EventBrite as my source, added it to my workspace and clicked it. Those beautiful questions I’ve come to know and love:
Same great natural language processing, same great visualizations
Writing about this is easy. Using data sets created from connecting to these sources is also easy. Watson Analytics treats data from them just as it treats data in a flat file. You ask questions and you get answers. I’ll show you how I did it. But first, my disclaimer: I wasn’t looking for anything in particular. I just wanted to see what I could do with data from EventBrite and HubSpot.
Here, I wanted to know what might cause disgusted reaction to the state of a venue. So, I simply asked Watson Analytics “What drives emotiondisgust?” I got my beloved spiral (I really am a predictive analytics kind of gal). Of course, it had all kinds of information about disgust:
Apparently, the state and the capacity of the venue is most likely to result in disgust. Interesting.
For this next visualization, I imported HubSpot data related to deals. I can’t say I was jumping up and down about my data quality score (38). But, I still wanted to see what kind of visualization I could get from a starting point. I clicked on the HubSpot card on my workspace and chose “What is the breakdown of Time Modified and Stage?” The correlation of time and stage sounded appealing. Watson Analytics produced a beautiful heat map of that information, but to me it looked like the breakdown was similar for each time:
As I was scanning the heat map I was intrigued by “Top Amount by Stage” in the exploration bar, so I clicked it. I got a much clearer representation of the deal amounts varied by stage. Not surprisingly, the highest amounts were at closing; however, it was interesting to see how they grew and that they actually have a value assigned to them when an appointment is scheduled.
How these data connectors can work for you
As you can see, thanks to data connectors, it’s just as easy to import data from the sources you use use every day as it is to upload spreadsheets. Just a couple of clicks and you’re looking at visualizations that could to lead to something big for you and your business.
If you’re interested in seeing how these data connectors can be used in business (and not by a blogger playing around), check out this video, which tells the story of how a marketer used this data to help put on a developer conference.
Data connectors are only available with Watson Analytics Professional Edition. But if you register now at www.watsonanalytics.com, you get a free 30-day trial and can try them yourself. Happy connecting!