Driven by specialized analytics systems and software, big data analytics can point the way to various business benefits, including new revenue opportunities, more effective marketing, better customer service, improved operational efficiency and competitive advantages over rivals. Big data analytics applications enable data scientists, predictive modelers, statisticians and other analytics professionals to analyze growing volumes of structured transaction data, plus other forms of data that are often left untapped by conventional business intelligence (BI) and analytics programs. That encompasses a mix of semi-structured and unstructured data -- for example, internet clickstream data, web server logs, social media content, text from customer emails and survey responses, mobile-phone call-detail records and machine data captured by sensors connected to the internet of things.
| Autorius: | M. Komala, K. R. Nataraj, K. R. Rekha, |
| Leidėjas: | LAP LAMBERT Academic Publishing |
| Išleidimo metai: | 2018 |
| Knygos puslapių skaičius: | 152 |
| ISBN-10: | 6139882109 |
| ISBN-13: | 9786139882106 |
| Formatas: | 220 x 150 x 10 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Advanced Multi-Access Memory for Big Data Analytics: Advance Memory Architecture using FPGA“
