Blog to help you become multi-disciplined, cross-functional design expert who can thrive in a consumer-focused, mission-driven, and fast-paced environment. Take a data-driven, customer-first approach to understanding the end-to-end customer journey and use the insights presented in the blog to help you develop relevant product roadmap considerations and go-to-market approaches.
Have read many times about the "bible belt". So, decided to take a quick look to see if this expression actually pans out. And as it turns out it does. Take a look for yourself.
You will see similar geographical distribution if you changed the search term to "Jesus" or "God".
In the just concluded Wimbledon Tennis Tournament IBM showcased some cool technology. IBM SlamTracker™ - a real time statistics and data visualization platform that leverages IBM's predictive analytics technology. It provides an ‘at a glance’ visual representation of a match using scores and statistics and encourages fans to get more involved by interacting with the data to gain deeper insight into the game. IBM SlamTracker™ analyses over eight years of Grand Slam data (over 41 million data points), to identify patterns in players and their styles. Before each match, IBM analyses historical matches between the players (or between players of similar styles if the players in question have not met before). In the last couple of years IBM did trial runs of SecondSight , which for the first time enabled the viewer to track the direction, speed and distance of players as they moved about the court. Data from SecondSight enables displays such as one below. Hopefully
Following is a great resource for any one considering different choices for their "NoSQL" style frame work. As always, "one-size-fits-all" approach does * not * work for NoSQL frameworks. Just as a side note that MongoDB, Cassandra and CouchDB are the top three skills sought out on indeed.com (popular aggregator of job boards) of all the databases in the table below. Having a large pool of talent is always a good thing for your technology choice. Source : International Journal of Database Theory and Application, NoSQL Database: New Era of Databases for Big data Analytics Classification, Characteristics and Comparison, A B M Moniruzzaman and Syed Akhter
One of the biggest issues in healthcare research is the inability of researchers to obtain meaningful healthcare related data easily. Information silos of healthcare data exist across both private and public sectors with almost no cross-team access. Its almost like multiple players trying to solve a puzzle with each player having one piece. Anyone who loves puzzles can see how difficult it can be if you can only see your own puzzle piece and none of the others. Believe me, it is frustrating! What is a data silo and why is it bad? Data silos is data that is aggregated from a few isolated data sources and accessible by one or a few related organizations. This can result in lack of transparency, efficiency and the kinds of applications that the data can be used for. This is true for any kind of data but is especially true for data in health care sector. Management of healthcare data in addition to having usual challenges of hard-to-obtain IT skills, limited b