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Computer Science Cloud Computing assignment

Please see attachment for details

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Note: To complete this template, replace the bracketed text with your own content. Remove this note before you submit your paper.]

Cloud Computing Evaluation Paper

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Cloud Computing

[Differentiate between cloud computing models and their uses. What are the different types of deployment models and service models? When is it appropriate to use each of the models, both deployment and service?]

Benefits and Drawbacks of the Cloud

[Compare the benefits and drawbacks of cloud deployment models versus on-premises models. What are the benefits of cloud deployment models versus on-premises models? What are the drawbacks of cloud deployment models versus on-premises models?]

Cloud Deployment Models

[Discuss the risks and benefits of adopting the different cloud computing deployment models. Identify some of the risks of adopting the different cloud computing deployment models. Identify some of the benefits of adopting the different cloud computing deployment models.]

Considerations of Cloud Computing

[Discuss considerations that should be taken into account when switching to a cloud model. What are some of the organizational issues that should be taken into account? What are some of the technical issues that should be taken into account?]

Big Data vs. Structured Data

[Explain what differentiates big data from structured data to stakeholders. Compare and contrast preprocessing methods for big data versus structured data. How is big data collected in comparison to structured data? How is big data stored in comparison to structured data? Explain the steps you took to complete uCertify Lab 1.3.2 (Subsetting a DataFrame). How did you create a subset of your data set? Why is it important to separate large data sets into smaller ones?]

uCertify Lab 1.3.2 (Subsetting a DataFrame).

Volume, Variety, and Velocity of Big Data

[Describe how the scale (volume, variety, and velocity) of big data affects data analysis methods. How does the scale of a data set affect its ability to be processed by conventional methods? How does the scale of a data set affect its usability? Explain the steps you took to complete uCertify Lab 1.2.2 (Grouping a DataFrame). How did you create the three separate values (mean weights)? How would this process be done if you were to calculate the value for hundreds of variables at once? How do the three Vs impact this work?]

uCertify Lab 1.2.2 (Grouping a DataFrame

References

[Include any references cited in your paper in full APA format. Don’t forget to include in-text citations as well.]

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