Difference between revisions of "Big Data Integration"
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| − | == | + | ==Module Information== |
| − | |||
| − | * | + | ===Module Objectives=== |
| + | * How to implement a cloud based storage solution for a company's big data needs | ||
| + | * The knowledge needed to integrate desktop and web applications to utilize web services and stored data. | ||
| + | * How cloud based DNS solutions can help to optimize a company's IT infrastructure | ||
| + | * How cloud based servers and service implementations can be easily deployed for rapid utilisation | ||
| + | * The steps involved in data exchange between web services and cloud based applications | ||
| + | |||
| + | ===Resources - References=== | ||
| + | * Programming Amazon EC2, Juirg van Vliet 1st 2011 O’Reilly | ||
| + | * Google Compute Engine, Marc Cohen 1st 2011 O’Reilly | ||
| + | * Python for Google App Engine, Massimiliano Pippi 1st 2015 Packet | ||
| + | * Big Data Fundamentals Concepts, Drivers & Techniques, Thomas Erl, Wajid Khattak, and Paul Buhler, Prentice Hall | ||
Revision as of 00:32, 14 February 2019
Module Information
Module Objectives
- How to implement a cloud based storage solution for a company's big data needs
- The knowledge needed to integrate desktop and web applications to utilize web services and stored data.
- How cloud based DNS solutions can help to optimize a company's IT infrastructure
- How cloud based servers and service implementations can be easily deployed for rapid utilisation
- The steps involved in data exchange between web services and cloud based applications
Resources - References
- Programming Amazon EC2, Juirg van Vliet 1st 2011 O’Reilly
- Google Compute Engine, Marc Cohen 1st 2011 O’Reilly
- Python for Google App Engine, Massimiliano Pippi 1st 2015 Packet
- Big Data Fundamentals Concepts, Drivers & Techniques, Thomas Erl, Wajid Khattak, and Paul Buhler, Prentice Hall
