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 product roadmap and go-to-market approaches.
For our corporate site visit https://biz.infoivy.com
Comparison chart for "SQL" interfaces for big data sets (Apache Drill, Impala, BigQuery and others)
In most big data shops the requests for data comes from applications that are either developed in-house or are configured for custom use. Hence the data query options are many. But in several companies with active and inquisitive data scientists and analysts there will be a steady stream of ad-hoc requests. These can be handled in many different ways. Following table compares the important features of various "SQL" type interfaces to provide ad-hoc access to large data sets. Choose your technology carefully since once in place it is not easy to make a switch.
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