| DC Field | Value | Language |
|---|
| dc.contributor.author | Ogunleye, J. | - |
| dc.date.accessioned | 2016-09-27T08:24:47Z | - |
| dc.date.accessioned | 2017-07-18T11:51:42Z | - |
| dc.date.available | 2016-09-27T08:24:47Z | - |
| dc.date.available | 2017-07-18T11:51:42Z | - |
| dc.date.issued | 2016 | - |
| dc.identifier.citation | Ogunleye, J. Predictive Analytics As Applied to Big Data: Considerations for Analytics Teams / J. Ogunleye // BIG DATA and Advanced Analytics. Использование BIG DATA для оптимизации бизнеса и информационных технологий : сборник материалов II международной научно-практической конференции, Минск, 15-17 июня 2016 г. / редкол. : М. П. Батура [и др.]. – Минск : БГУИР, 2016. – С. 28-36. | ru_RU |
| dc.identifier.isbn | 978-985-543-237-2 | - |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/9025 | - |
| dc.description.abstract | The phenomenon of big data has brought home the importance of predictive analytics
as a technology and statistical technique critical to taking the sting out of the big data mayhem.
Although predictive analytics has been around for some time, the benefits of predictive analytics have
only recently been appreciated due largely to the phenomenon of big data. This new-found
appreciation of predictive analytics is coupled with a desire by many corporate organisations not only
to inform strategic business decisions with evidence, but also to predict future trends with a high level of confidence. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | БГУИР | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | predictive analytics | ru_RU |
| dc.subject | data quality | ru_RU |
| dc.subject | limitations | ru_RU |
| dc.subject | model and modelling | ru_RU |
| dc.title | Predictive Analytics As Applied to Big Data | ru_RU |
| dc.type | Article | ru_RU |
| Appears in Collections: | BIG DATA and Advanced Analytics. Использование BIG DATA для оптимизации бизнеса и информационных технологий (2016)
|
