Question

Paper Requirements:   Review the section on the definitions of maturity stages and dimension variables in the CEO Technology Best Practices Arc.  Define each of the maturity stages and performance dimensions.  What are the key concepts from each section?  2pages APA format with reference 

Assignment and memo

 

1.Assignment

  • identify and apply the different analysis and design methods for business applications;
  • operate effectively within a team environment demonstrating team building and project management skills in information systems analysis and design; and
  • communicate information effectively in presentations with oral, written and electronic formats using media formats widely adopted for information systems development in business and government.

Create an alternative decision matrix for the case system. Using Excel or Word, develop a decision matrix to be used to evaluate three proposed design alternatives (alternatives A, B, and C).

The idea is to create a worksheet that can be applied to any set of alternatives.

Criteria: Decision matrix has columns for criteria weights and points available, and columns that represent three proposals. Within each proposal include columns for points assigned and

the product of points assigned times criteria weight. The bottom row of the matrix contains column totals.

Your essay should be 3 pages in content and fully explore all of the following items described above. Include at least 2 outside citations (not including your text) and use proper APA formatting.

Atleast 2 In-line citations and references required.

2. Weekly Memo – Memo should be related to the discussions , assignment and should be one page(citations,references, APA not required).

Strategic Plans

Describe how a strategic plan for information technology can differ across organizations. 

Provide a real-world example. 

  1. In your first paragraph describe how a strategic plan for information technology can differ across organizations. Use examples in your description.
  2. In your second paragraph, use the example in the posting and discuss how an information technology strategic plan for a global company may differ than for a national (US) company.
  3. In the third paragraph, provide a real-world example, based upon the examples used in the first post.

project 3

 

Class Discussion Topics

prepare 2 slide powerpoint for each question with diagram too 

  1. Discuss the pros and cons of the memory management schemes presented in this chapter. If given an option, which scheme would you implement and why?
  2. Discuss the difference between associative memory and cache memory and the steps involved in using these types of memory.
Projects

write 2 page paper for each question 

  1. Choose an operating system and submit a report on approaches to manage its virtual memory.  
  2. Working in teams of four, write pseudocode for the first-in-first-out (FIFO) and least-recently-used (LRU) page replacement policies.

KPIs

  

300 words minimum, word document

Assignment Instructions:

Explain KPIs what are they, as they apply to web analytics.

Explain your position if you agree or disagree with their relevance in web analytics.

Explain your position.

Use the following links for references:

https://www.kaushik.net/avinash/insights-web-analytics-kpi-measurement-techniques/

https://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/

https://www.kaushik.net/avinash/best-web-metrics-kpis-small-medium-large-business/

https://www.kaushik.net/avinash/measure-choose-smarter-kpis-incentives/

https://www.datapine.com/kpi-examples-and-templates/google-analytics

Legislated Privacy concerns

 

Go to the website: https://epic.org/privacy/litigation/ which focuses on civil rights issues and privacy. Pick a case.

Using WORD, in your OWN WORDS, write an ORIGINAL brief essay of 300 words or more  :

  • Summarize the case
  • Give your opinion of the decision.
  • Describe how the case deals with the material in this chapter

web dev

 

Based on the feedback from your earlier drafts, make any changes necessary. You will continue to work on your site adding the following elements:

  • Use CSS to position content on at least two pages
  • Add a special effect using CSS on the Homepage
  • Use CSS to “brand” your form

Now that you have begun to write your pages in HTML, please add the following to a comment in the of your work:

  • Name, date, week #, class with section, and campus # (i.e. CIS273001VA016)

Always zip your work into a single folder for uploading to Blackboard. You’ll want to keep each week separate so that you can review earlier iterations of your site, in case you want to revert something back based on feedback from your professor.

Exploratory Analysis with What-If Tool

In this individual assignment, you will perform an exploratory analysis with What-If Tool, to better understand the structure of datasets, investigate initial questions, and develop preliminary insights and hypotheses. Your final submission will take the form of a report consisting of key insights gained during your analysis.

Step 1: Dataset Selection and Initial Questions

Pick two datasets. These can be ones that are available for demo at https://pair-code.github.io/what-if-tool/explore/ (Links to an external site.). But we’ll give you additional points if you choose to use datasets that are not available there.  

After selecting datasets – but prior to analysis – write down an initial set of three questions you’d like to investigate about the datasets and prediction results from ML models.

Part 2: Exploratory Visual Analysis

Next, you will perform an exploratory analysis of your dataset and results from ML models using What-If Tool. You can either use their web demo if you use their provided datasets. You can also use notebooks and revise them with your datasets and models.

You should consider two different phases of exploration.

In the first phase, you should seek to gain an overview of the structure of your datasets and results from their models. What is the structure of datasets? Which features are used? Are there any notable issues with the distributions of datasets? What is the model performance? What features contributed the most? Are there any surprising relationships among subsets of data and model results? Are there any fairness issues?

In the second phase, you should investigate your initial questions, as well as any new questions that arise during your exploration. For each question, playing with the visualizations in What-If Tool, that might provide a useful answer. Interact with their functionalities (e.g., datapoint editors, dropdown menus, fairness analysis) to develop better perspectives, explore unexpected observations, or sanity check your assumptions. You should repeat this process for each of your questions, and also feel free to revise your questions or branch off to explore new questions.

What to submit?

You’ll submit a single PDF as a form of a report. For each dataset, you will provide 10 most interesting or surprising findings (or “insights”) with details and screenshots. Your “insights” can include important surprises or issues (such as skewed data distributions, critical fairness issues) as well as responses to your analysis questions. Each finding will consist of a title and 2-4 sentence descriptions, and screenshots. Provide sufficient detail so that anyone could read through your report and understand what you’ve learned. You are free, but not required, to annotate your images to draw attention to specific features of the data. 

Do not submit a report cluttered with everything little thing you tried. Submit a clean, succinct report that highlights the most interesting, insightful observations. You don’t need to tell us how the tool works — we already know that. Think of this like a report to your manager who wants to know what the datasets look like and how the model worked. 

The structure of the report will be:

  • Dataset 1
    • Which dataset?
    • Three initial questions
    • 10 most interesting findings
  • Dataset 2
    • Which dataset?
    • Three initial questions
    • 10 most interesting findings

Grading

  • Clear questions applicable to the chosen datasets
  • Clearly written, understandable descriptions that communicate primary insights
  • Sufficient breadth of analysis, exploring multiple questions
  • Sufficient depth of analysis, with appropriate follow-up questions
  • Interesting insights that are worth reporting