Big Data applications: Making them deliver value
| dc.contributor.author | Self, Richard | |
| dc.date.accessioned | 2016-11-14T10:32:14Z | |
| dc.date.available | 2016-11-14T10:32:14Z | |
| dc.date.issued | 2016-09-28 | |
| dc.identifier.citation | Self R. (2016) 'Big Data applications: Making them deliver value' Software Testing Conference North, The Royal York Hotel, York, 27-28 September | en |
| dc.identifier.uri | http://hdl.handle.net/10545/620822 | |
| dc.description.abstract | This session will use a governance framework consisting of the 12 Vs of Big Data to pose important questions that should be considered in order to ensure successful implementation of value creating applications, especially those involving Big Data. It will cover relevant aspects of the design, development, testing and implementation cycle. Testing software has often been used as the gatekeeper for inadequacies in the analysis, design and coding processes and has been used to engineer quality back into a product. This is extremely expensive and time consuming. There are more effective ways of developing software. The current climate of apparently perpetual regular beta releases of apps can lead to significant reputational risks for businesses, hence the importance of considering the overall cycle as part of the software testing perspective in order to ensure business success. | |
| dc.language.iso | en | en |
| dc.relation.url | http://north.softwaretestingconference.com/ | en |
| dc.subject | Big Data analytics | en |
| dc.subject | Data processing | en |
| dc.title | Big Data applications: Making them deliver value | en |
| dc.type | Presentation | en |
| dc.contributor.department | University of Derby | en |
| dc.relation.embedded | <iframe width="560" height="315" src="https://www.youtube.com/embed/NVgxqeDeayw" frameborder="0" allowfullscreen></iframe> | en |
| html.description.abstract | This session will use a governance framework consisting of the 12 Vs of Big Data to pose important questions that should be considered in order to ensure successful implementation of value creating applications, especially those involving Big Data. It will cover relevant aspects of the design, development, testing and implementation cycle. Testing software has often been used as the gatekeeper for inadequacies in the analysis, design and coding processes and has been used to engineer quality back into a product. This is extremely expensive and time consuming. There are more effective ways of developing software. The current climate of apparently perpetual regular beta releases of apps can lead to significant reputational risks for businesses, hence the importance of considering the overall cycle as part of the software testing perspective in order to ensure business success. |