Embedded Tableau Oscars Dashboard

(This post was originally published on BIHappy Blog)

A few months ago I published my Oscars dashboard (http://bihappyblog.com/2014/03/10/oscars-dashboard/). Recently, I decided to produce a new version of it, leveraging Tableau, and extending it with some additional features possible with some html5 integration. Embedding Tableau in an external web application framework is a great way to leverage Tableau terrific data exploration features like drilling, grouping and filtering with some intuitive, simple to understand and use interface suitable for a user’s portal or an executive audience. This example leverages my Oscars database file and allows exploration of Oscar nominated actors, actresses, directors as well as a free form exploration option for perusing more of the data set. Enjoy..

Tableau connected Medicare enrollment dashboard

(This post was originally published on BIHappy Blog)

Our medicare enrollment database continues to grow and now contains over 9M enrollment records across the country. I began collecting this information almost two years ago with my colleague Josh Tapley, and we used it to produce our medicare advantage dashboards using the SAP Dashboards (Xcelsius) tool, as well as our HTML5 reporting solution. Aside from being an interesting dataset, relevant to medical insurance professionals and anyone else interested in medicare and healthcare, this platform provides us the medium to demonstrate many technical advantages and techniques we often solve on projects. So, to add to our arsenal or medicare advantage dashboards, I have now added a Tableau version. This version looks and operates just like it’s siblings from SAP and our custom HTML solution, however uses completely different technology under the covers. To create it, we had to overcome several interesting challenges, from the ability to serve up Tableau content from our secure server which resides behind our firewall via secure proxy to the internet, addressing proxying, authentication and security challeneges to the ability to create visuals which do not exist natively in the tool, such as a donut chart. This dashboard is connected to the live data, and executed a query each time a state is selected. This design pattern is consistent across all three versions of this dashboard and is designed to demonstrate the ability to work with these dashboarding tools in a completely “hands free” no hassle, and no maintenance mode, where data is refreshed in the database and automatically reflected in the dashboard with no need for any intervention. Enjoy.

Google chairman notes the arrival of big data and machine intelligence everywhere

In a rare interview, Google Chairman Eric Schmidt gives Bloomberg his outlook for 2014 trends (http://www.bloomberg.com/video/ask-a-billionaire-eric-schmidt-s-2014-predictions-pmV~qd7qTeipbjKx6_wW1Q.html). In this 2 minutes video, Schmidt talks about several obvious trends, like “everyone will have a smart phone… essentially connected to a super computer”. Another important remark Schmidt made is about the “arrival of big data and machine intelligence everywhere”.

It is not about the invention of big data and machine intelligence. It is about the arrival. I find that to be the essence of the big data revolution. The idea that we can leverage computers and technology to process data and derive information and intelligence from thatdata is certainly not new. However, it has been hampered by slow processors, lack of storage capabilities, and inability to amass sufficiently significant amounts of data to deliver this intelligence. Past attempts to overcome the technology shortfalls have been painful and could only deliver meaningful results when applying large investments. Well, all that is changing now. It is now affordable and relatively simple to perform analytical tasks that were considered extremely challenging only a few years ago. My news analytics experiment is one example of that (http://bihappyblog.com/2013/12/05/predicting-the-news-with-sap-hana/). IT departments and organizations are finding that barriers that prevented them from delivering google like level of services are quickly disappearing, and the bar set by consumer web sites for level of service, sophistication and relevance can now be met with of enterprise applications. This is the challenge we in the BI industry will have to face and meet over the next few years. I believe that leveraging the knowledge and understanding developed during decades of data warehousing development to overcome technological impossibilities positions us, the BI industry veterans in a unique position to help drive the big data revolution in the corporate world. Modeling, abstraction skills, problem solving and technical know-how are the building blocks needed for any big data related project, and these are the traits of the trade for us in the BI industry.