Tools to tackle big data challenges with MATLAB
| Date | Contributor | Description | Rating |
|---|---|---|---|
| 17 Jul 2013 | Sarah Wait Zaranek |
Big data represents an opportunity for analysts and data scientists to gain greater insight and to make more informed decisions, but it also presents a number of challenges. Big data sets may not fit into available memory, may take too long to process, or may stream too quickly to store. Standard algorithms are usually not designed to process big data sets in reasonable amounts of time or memory. There is no single approach to big data. Therefore, MATLAB provides a number of tools to tackle these challenges. |
| Tag | Applied By | Date/Time |
|---|---|---|
| cluster | Beaver | 30 Jul 2013 at 10:35pm |
| cloud | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |
| distributed | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |
| cluster | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |
| 64-bit | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |
| gpu | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |
| textscan | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |
| large data | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |
| big data | Sarah Wait Zaranek | 17 Jul 2013 at 12:39pm |