CIS 512 Week 6 Case Study 2

Published on December 2017 | Categories: Business/Law | Downloads: 83 | Comments: 0 | Views: 1008
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CIS 512 Week 6 Case Study 2 Click Link Below To Buy: https://hwaid.com/shop/cis-512-week-6-case-study-2/ Contact Us: [email protected] CIS 512 Week 6 Case Study 2 – How Will Astronomy Archives Survive the Data Tsunami Astronomers collect and generate petabytes of data. The volume of data is currently growing at a rate of 0.5 PB per year. The projections indicate that by 2020, more than 60 PB of archived data will be available to astronomers. Read the paper, “How Will Astronomy Archives Survive the Data Tsunami?”, located in Week 6 of the online course shell. Write a four to five (4-5) page paper in which you: Analyze and assess the performance degradation issues highlighted in the case study. Evaluate the archival techniques that are outlined in the study, such as cloud storage. Determine why they are not able to handle the growth of the archived data. Evaluate the emerging technologies, such as clustering, discussed in the case study, which could be applied to the data archival problem. Related

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CIS 512 Week 6 Case Study 2 Click Link Below To Buy: https://hwaid.com/shop/cis-512-week-6-case-study-2/ Contact Us: [email protected] CIS 512 Week 6 Case Study 2 – How Will Astronomy Archives Survive the Data Tsunami Astronomers collect and generate petabytes of data. The volume of data is currently growing at a rate of 0.5 PB per year. The projections indicate that by 2020, more than 60 PB of archived data will be available to astronomers. Read the paper, “How Will Astronomy Archives Survive the Data Tsunami?”, located in Week 6 of the online course shell. Write a four to five (4-5) page paper in which you: Analyze and assess the performance degradation issues highlighted in the case study. Evaluate the archival techniques that are outlined in the study, such as cloud storage. Determine why they are not able to handle the growth of the archived data. Evaluate the emerging technologies, such as clustering, discussed in the case study, which could be applied to the data archival problem. Related

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