With the latest addition to our public demos, we have the absolutely spectacular 1.2 billion row taxi/limo/uber/lyft dataset from NYC. The dataset is comprised of staggering detail (full GPS, transaction type, passenger counts, timestamps) from January 2009 through June 2015 (essentially the birth of rideshare).
The old cliché that records are meant to be broken certainly applies to the tech industry. They‘re milestones that reset the bar for what’s possible but more importantly serve as a barometer of where things are headed.
The rise of modern business intelligence (BI) has seen the emergence of a number of component parts designed to support the different analytical functions necessary to deliver what enterprises require.
Earlier today the Business Intelligence Group announced its Startup of the Year Award for 2016 and selected MapD as a winner in that category.
On Friday, Amazon announced the availability of large GPU instances on AWS marking a new chapter in the GPU revolution.
Speed is increasingly defining the user experience from B2C to B2B. No matter how attractive the application, if it does not perform from a speed perspective, it might as well be ugly because that is the sentiment increasingly attached to slow, plodding applications on the web, mobile and in the enterprise.
Having made the improbable jump from the game console to the supercomputer, GPUs are now invading the datacenter. This movement is led by Google, Facebook, Amazon, Microsoft, Tesla, Baidu and others who have quietly but rapidly shifted their hardware philosophy over the past twelve months.
As we enter the final stretch of our summer, it is time to start looking ahead to the conference-rich third and fourth quarters. After a period of relative calm, we are back with a vengeance, starting almost immediately.
In the dataworld, there is a particular dataset, referred to as “the taxi dataset,” that has been getting a disproportionate amount of attention lately.