DAT 260 Project One Guidelines and Rubric
Competencies
In this project, you will demonstrate your mastery of the following competencies:
· Explain the concepts of cloud-based architectures
· Differentiate between the functions of big data technologies
Overview
As you have learned, cloud environments can be used to host, maintain, and analyze large volumes of information. As a data analyst, you must be able to evaluate cloud environments compared to traditional ones, including capacity, costs, the benefits and drawbacks of cloud computing, and the risks and benefits of transitioning. In this project, you will explain what big data is and why it requires different data analysis methods than traditional approaches.
Directions
Use the template linked in the What to Submit section to prepare a cloud computing evaluation paper. As you complete each section of the template, consider the following rubric criteria:
1. Differentiate between cloud computing models and their uses.
A. What are the different types of deployment models and service models?
B. When is it appropriate to use each of the models, both deployment and service?
2. Compare the benefits and drawbacks of cloud deployment models versus on-premises models.
A. What are the benefits of cloud deployment models versus on-premises models?
B. What are the drawbacks of cloud deployment models versus on-premises models?
3. Discuss the risks and benefits of adopting the different cloud computing deployment models.
A. Identify some of the risks of adopting the different cloud computing deployment models.
B. Identify some of the benefits of adopting the different cloud computing deployment models.
4. Discuss considerations that should be taken into account when switching to a cloud model.
A. What are some of the organizational issues that should be taken into account?
B. What are some of the technical issues that should be taken into account?
5. Explain what differentiates big data from structured data to stakeholders.
A. Compare and contrast preprocessing methods for big data versus structured data.
B. How is big data collected in comparison to structured data?
C. How is big data stored in comparison to structured data?
D. 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?
6. Describe how the scale (volume, variety, and velocity) of big data affects data analysis methods.
A. How does the scale of a data set affect its ability to be processed by conventional methods?
B. How does the scale of a data set affect its usability?
C. 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?
What to Submit
To complete this project, you must submit the following:
Cloud Computing Evaluation Paper
Use the Project One Template to create your evaluation paper assessing cloud computing. Replace the bracketed text in each section with your responses. Each section should be 1 to 2 paragraphs long, for 3 to 4 pages. All sources should be cited according to APA style.
