IT513-15 Part A,B - Storage Hierarchy and Secondary

IT-513-15 Enterprise IT Application and Business Analytics

Part A :

1. Question: Storage Hierarchy and Secondary Storage Devices
Explain the concept of storage hierarchy in computer systems, and describe the primary characteristics of secondary storage devices. Compare and contrast two different types of secondary storage devices in terms of their advantages, disadvantages, and typical use cases. Provide examples of situations where choosing the appropriate secondary storage device is crucial for optimizing data management in computing environments.

2. Question: Data Transfer Rate and Disk Access Times
Define data transfer rate and disk access times in the context of computer peripherals. Discuss the factors that influence these performance metrics for storage devices. How do the characteristics of storage devices impact the overall system performance? Illustrate with real-world examples, and explain the strategies that can be employed to improve data transfer rates and reduce disk access times for various applications.

3. Question: GPU Technology and Display Resolution
Explore the role of Graphical Processing Units (GPUs) in modern computing systems, especially in relation to display resolution and picture size. Describe how GPUs contribute to enhancing graphics performance and enabling high-quality visuals. Discuss the factors that affect display resolution and how it relates to the capabilities of GPUs. Highlight the importance of GPU technology in applications such as gaming, multimedia, and professional graphics work, and provide insights into the trends shaping GPU development.

Part B : Data analytics is the process of examining, cleaning, transforming, and interpreting data to discover meaningful insights, patterns, and trends that can inform decision-making and drive business or organizational outcomes. As we begin to explore the various techniques and tools to extract valuable information from large sets of data, whether structured (e.g., databases) or unstructured (e.g., text documents, social media posts), we must also be conscious about the various forms of our own personal bias (i.e. Selections, Sampling, Measurement, Response, Algorithmic, Confirmation, Historical, Ethical, etc.) that may lead to unfair, incomplete, or misleading results and decisions.

For this assignment, use your favorite search engine to search for forms of bias in data analytics. Choose at at least one form of bias and and post the following:

• A post must that is at least 200 words.
• Discuss your chosen bias (what it is and how it occurs)
• Potential negative outcomes
• Options to remedy
• At least one example