There is widespread agreement that the Internet of Things will be a transformative factor in the business use of information. The prospect of billions of connected devices promises to transform home activities, transportation, industrial operations, and many other aspects of our lives.
The bad news about the IoT is that we have a lot of work to do before we are ready for it. We’ve got to up our games considerably with regard to data management and analytics if we’re going to capture, store, access and analyze all the IoT data that will be flowing around the Internet. The good news (in addition to its potential) is that most organizations have a few years to get better at these capabilities before the real onslaught hits. The sensor devices, IoT data standards, and data management platforms are still in their relatively early stages, and no customer, business partner, or CEO could reasonably expect that you could tame all that IoT data today.
Google today announced a significant enhancement to the developer tools for its Google Cast software, which lets people stream media from their PCs and mobile devices to TVs and speakers. The Google Cast software development kit (SDK) Developer Console now includes dedicated pages for analytics for apps that work with Google Cast.
The tool is a bit reminiscent of Google Analytics, which lets people see check website performance and usage. Developers can access it by clicking the View link under the Statistics column for a given app.
“The devices tab shows the number of Cast devices that have launched your application, the sessions tab shows the number of Cast sessions of your application, and the average playback tab shows the average length of media playback time per session for your application,” Google Cast software engineer Chris Dolan wrote in a blog post. Developers can break things down by geography and operating system and change the time range.
Smart Data Collective: A moderated business community for BI, predictive analytics, and data professionals.
Data Science 101: A blog for learning to be a data scientist.
Revolution Analytics Blog: A blog dedicated to news and information of interest to members of the R community.
Geeking with Greg: A very informative weblog by Greg Linden
Shape of Data: A blog to explore the geometry behind machine learning, data mining, etc.
What’s the Big Data: A blog to explore big Data and business
FiveThirtyEight Blog: A blog by Nate Silver for exploring analytics on politics, sports, and more
Users who have LIKED this post:
Predictive Analytics Innovation Summit, March 2-3, Melbourne, Australia
Big Data and Analytics Summit, March 2-3, Singapore
Gaming Analytics Summit, March 3-4, London, UK
European Smart Grid Cyber Security, March 7-8, London, UK
Big Data Paris, March 7-8, Paris, France
2nd Global Data Science Conference, March 7-9, Santa Clara, CA
Structure Data, March 9-10, San Francisco, CA
Internet of Things Forum, March 9-10, Cambridge, UK
10th Sloan MIT Sports Analytics Conference, March 11-12, Boston, MA
IEEE International Conference on Big Data Analysis (ICBDA 2016), March 12-14, Hangzhou, China
Gartner Business Intelligence & Analytics Summit, March 14-16, Grapevine, TX
Discovery Summit Europe, March 14-17, Amsterdam, The Netherlands
The Internet of Things Conference, March 14-17, Munich, Germany
Re:Work Connected City Summit, March 16-17, London, UK
HR and Workforce Analytics Summit, March 16-17, London, UK
Data Innovation Summit, March 22, Stockholm, Sweden
Industrial IoT, March 23-24, London, UK
2nd IEEE Conference on Big Data Computing Serivce and Applications, March 29-April 1, Oxford, UK
Users who have LIKED this post: