Please review the attached file.
Info Tech WK7
Q1. 275 words
What is a project, and what are its main attributes? How is a project different from what most people do in their day-to-day jobs? Discuss the importance of top management commitment and the development of standards for successful project management. Provide examples to illustrate the importance of these items based on your experience on any type of project. Discuss the unique challenges that an IT project presents.
Q2. Research paper ——SEPARATE DOCUMENT —– 9 full pages
This week it is a written activity is a three- part activity. You will respond to three separate prompts but prepare your paper as one research paper. Be sure to include at least one UC library source per prompt, in addition to your textbook (which means you’ll have at least 4 sources cited).
1. Start your paper with an introductory paragraph. 1 page
2. Below 3 prompts
Prompt 1 “Data Warehouse Architecture” (2 pages): Explain the major components of a data warehouse architecture, including the various forms of data transformations needed to prepare data for a data warehouse. Also, describe in your own words current key trends in data warehousing.
Prompt 2 “Big Data” (2 pages): Describe your understanding of big data and give an example of how you’ve seen big data used either personally or professionally. In your view, what demands is big data placing on organizations and data management technology?
Prompt 3 “Green Computing” (3 pages): One of our topics in Chapter 13 surrounds IT Green Computing. The need for green computing is becoming more obvious considering the amount of power needed to drive our computers, servers, routers, switches, and data centers. Discuss ways in which organizations can make their data centers “green”. In your discussion, find an example of an organization that has already implemented IT green computing strategies successfully. Discuss that organization and share your link. You can find examples in the UC Library.
3.Conclude your paper with a detailed conclusion section. 1 page
Paper requirements
The paper needs to be approximately 9 pages long, including both a title page and a references page (for a total of 11-12 pages). Be sure to use proper APA formatting and citations to avoid plagiarism.
• Be approximately seven to ten pages in length, not including the required cover page and reference page.
• Follow APA7 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.
• Support your answers with the readings from the course, the course textbook, and at least three scholarly journal articles to support your positions, claims, and observations, in addition to your textbook. The UC Library is a great place to find supplemental resources.
• Be clearly and well-written, concise, and logical, using excellent grammar and style techniques. You are being graded in part on the quality of your writing.
Do the needful
Do the needful in the attached doc Qualitative_format.docx
Please write the quality content. This is for Ph.D. dissertation.
Discussion: Through the Looking Glass
Unit 2 Discussion: Through the Looking Glass
Unit 2 Discussion: Through the Looking GlassThis unit talks about perception, and what influences how we think of ourselves.How did watching the video about stranger’s interpretations of each other influence your thoughts on self-identity?
(Utilize the components of identity from chapter 3 to add credibility to your response.)What steps could you take personally to enhance your self-esteem and self-identity?
(Cite information from your textbook to back your response.)
Robotics, Social Networks, AI and IoT Assignment
Complete the following assignment in one MS word document:
Chapter 12 –discussion question #1-3 & exercise 1 & 12 & 16
When submitting work, be sure to include an APA cover page and include at least two APA formatted references (and APA in-text citations) to support the work this week.
All work must be original (not copied from any source).
Discussion questions:
1. Some people say that chatbots are inferior for chatting. Others disagree. Discuss.
2. Discuss the financial benefits of chatbots.
3. Discuss how IBM Watson will reach 1 billion people by 2018 and what the implications of that are.
Exercise questions:
1. Compare the chatbots of Facebook and WeChat. Which has more functionalities?
12. Research the role of chatbots in helping patients with dementia.
16. Microsoft partners with the government of Singapore to develop chatbots for e-services. Find out how this is done.
SE493 week 3A
Assignment Description
Please read chapter 5 textbook and review page 42 to 46 PP slides Chapter 5, (Examples of Application Types).
1) Transaction processing applications/systems? (Provide couple of examples).
2) Data Processing Applications/systems? (provide couple of examples)
database project
Hi, I have a simple project for the database material. The attached file contains the solution, but I want another solution
Usability Category Paper – Memorability
please write 5 pages Literature review paper on Memorability (Human Comput Inter & Usability) including references.
Thanks!
discussion
refer to the attached details
Assignment
While this weeks topic highlighted the uncertainty of Big Data, the author identified the following as areas for future research. Pick one of the following for your Research paper:
- Additional study must be performed on the interactions between each big data characteristic, as they do not exist separately but naturally interact in the real world.
- The scalability and efficacy of existing analytics techniques being applied to big data must be empirically examined.
- New techniques and algorithms must be developed in ML and NLP to handle the real-time needs for decisions made based on enormous amounts of data.
- More work is necessary on how to efficiently model uncertainty in ML and NLP, as well as how to represent uncertainty resulting from big data analytics.
- Since the CI algorithms are able to find an approximate solution within a reasonable time, they have been used to tackle ML problems and uncertainty challenges in data analytics and process in recent years.