Sentence examples for high speed analytics from inspiring English sources
High Speed Analytics using advanced cloud services will increasingly be used as a complement to existing information management systems and programs to tame the massive data explosion.
High-speed analytics using advanced cloud services will increasingly be used as a complement to existing information management systems and programs to tame the massive data explosion.
Yet, whereas data once required a large team of skilled analysts to be made useful, today there are a number of enterprise level tools for running high speed data analytics on massive amounts of data, as well as publically available free tools like Google Analytics that offer every business and entrepreneur the opportunity to incorporate data analytics when making decisions.
The availability of cheaper sensors and connectivity, as well as the emergence of industrial strength platforms to digest and run analytics on high speed and large scale streams of data, will enable intelligent digital solutions across the energy industry.
To do this successfully demands high-speed data analytics.
This capability is relevant for areas such as high-speed data analytics, network processing, security functions and low power processing for IoT and Space.Reconfigure.io has developed a core platform allowing the acceleration of key compute demands with such FPGA technology by for the first time making it readily accessible to engineers.
I believe that's true for a lot of things -- including high-speed data analytics.
High-speed data analytics have garnered a lot of digital ink in the last half-decade or so.
As big data continues to build up and high-speed data analytics evolve proportionally, the major challenge will be refining all this data.
The term "high-speed data analytics" refers to the leveraging of raw data and converting it into actionable knowledge and insights.
High-speed data analytics have to meet this challenge by not only separating the good data from the bad, but by accounting for how the bad data might impact your overall conclusions.
