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It’s the easiest way to get started with Azure.
Our findings suggest that job security is a strong predictor of both IT career optimism and career planning ability.
High-skill jobs in services are primarily considered good if the work is interesting, while salary level and career opportunities count less.
Our results also shed lights on the potential approaches to improving developer retention.
We conclude that the career development strivings strategy has great potential as a flexible and efficient tool for use in career development research and practice.
confirmed that Microsoft Azure ML platform can be used to build effective SA models that can be used to perform data analytics.
We have, for the first time, created an open-architecture-based system named Crayons for Azure cloud platform using state-of-the-art techniques.
In addressing environmentally induced career change, the career development practitioner is better informed by a career development model than more traditional approaches.
Furthermore, there is a positive relationship between skill development and career development.
We conclude that further research is important for understanding how different actors within the career ecosystem can help to ensure that the conditions for sustainability are met in view of creating a more resilient career system.
Overall, the scale is a valid model of career development.
The authors suggest that the career assessment of ethnic minority women presents some special challenges for the career counselor.
These findings carry implications for career construction theory and human resource managers' career development in China.
The comprehensive tools and functionality of Windows Azure made it an ideal platform to develop and deploy this kind of service oriented applications.
This work provides a framework enabling us to understand career adaptation, and ‘mobile career’ phenomena such as careers based on project work and the role of overseas experience in career development.
Open accessJournal ArticleDOI
01 Sep 2013
55 Citations
Extensive experiments on Windows Azure with real and synthetic workloads validate the scalability and benefits of Now!
By making it easier for developers to use the predictive models in end-to-end solutions, Azure Machine Learning enables actionable insights to be gleaned and operationalized easily.
We also provide an open-source generic application framework that can be a starting point for application development for bag-of-task applications over Azure.
The integration of the two platforms will allow users to leverage the power of Windows Azure Platform for Aneka Cloud Computing, employing a large number of compute instances to run their applications in parallel.
Open accessProceedings ArticleDOI
21 Jun 2010
140 Citations
Although the discussion and analysis is tailored to scientific applications, the results are broadly applicable to the range of existing and future applications running in Windows Azure.