Assignment Preparation: You have been selected to run a major project for management of data at Big Online University. (Information on Big Online University listed below) Week 1 Scenario You have a challenge in your project: you do not have a team, a process for development, or any tools for data management with which to do the job. You need to develop a plan for them. Write a 1- to 2-page paper that addresses the following points: Define at least five key roles for members of your team involved in the definition, creation, and maintenance of the database and applications that use it. Give a job description of each role, with the skills and levels of education or certification you expect in each role, along with the major tasks that each team member will be expected to perform. Use salary information from referenced sources to suggest a range of possible salaries.Describe the major tasks that the team will perform, and the natural order of doing those tasks the first time.Explain key tools that team members must have to perform this job.Individual Project BIntroductionThe project is fictional. Any resemblance to any real organization is purely coincidental.Organization DescriptionBig Online University (BOU) has over 100,000 students, all of them attending online. It has many existing systems and databases used to track students, course registration, grades, finances, etc.You have been brought in to develop a database for the office of assessment, as part of a program to help BOU evaluate the student success of its programs.Information NeedsEvery program at the university has learning objectives, which define broad areas of skill or knowledge that students should have upon graduation. There are additional objectives associated with the common curriculum that all students need to achieve.A student may be in one or multiple programs (e.g., as a major or minor area, or a certificate program). Each program is comprised of both required and elective courses.The office of assessment arranges for students’ learning to be measured either directly (through assignments in the curriculum itself, or through outside tests), or indirectly (through the evaluation of student learning by the students themselves, or in surveys of employers or faculty members).The database must track student learning information, as well as a range of facts about items that might have influenced that learning, like particular courses or versions of courses that the students took, or the background of the students before they arrived (e.g., how did they perform in high school, are they working in the field that they are studying, how did they score on evaluations done at entry to the university?).The database must also track actions that were taken to improve programs, and which courses were affected by them (and in which versions). This can be useful for understanding if the changes were effective.Common TransactionsThe database has far more activity in addition to data than in conventional access to data. Information about new students needs to be added as they are accepted (since this is a four year school, about 25% of the total students are in each class, and most of these are added in a large batch from the admissions database just prior to the beginning of the school year, when it is known which students will attend. The information for a small number of transfers, including records from other universities, must also be added.There will also be a large quantity of new information from direct assessments, concentrated in the two weeks that end the two semesters. Roughly one class in five has some assessment data generated for each student, and the typical student takes 10 courses a year. The volume of information from indirect assessments is much smaller, with a sample of about 10,000 surveys (between current students, alumni, employers, and faculty each year, and these are spread throughout the year.Updates are made to courses taken by students as they add, drop or complete them.Each semester, the office produces statistical reports about the learning of all current students for each program.Historical ReportingMuch of the use of assessment office data involves historical analyses with data from this database, often combined with other sources. The university wants to understand which versions of programs produced the highest learning success, whether programs are effective for students who currently work in the field, or for those who do not, whether there are certain indicators in the backgrounds of students that indicate whether they are likely to learn, or even graduate, etc. The university may also need to understand where in the curriculum students are learning (since some learning objectives may be partially covered in several different courses.)Other Data SourcesThe university has information about how students performed in particular courses, whether they graduated, how long it took to do so, etc. Indeed, since the courses are all online, the university can potentially track every action in every class (how much time did the student spend reading the texts, how often did the student participate in discussions, which problems did the students answer incorrectly on the automated math tests, etc.). The challenge is mostly to determine what is useful.There is also outside information about student loan defaults, salaries that alumni obtain, what fields they may be working in (e.g., you can see this on LinkedIn). All of these may potentially be useful in understanding what kinds of students succeed in learning and applying their education.

OverviewTo understand and make use of any database system, you must learn various techniques associated with the fundamental operations of create, read, update, and delete (CRUD). For this assignment, you will begin by creating databases of document collections and performing basic reading or querying operations to retrieve specific documents from the database system. You will also gain practice updating documents and subdocuments, and removing documents from a database. You will use the mongo shell and mongoimport commands to complete this assignment.Note: Since this is the only assignment for Module Two, it is longer than a typical assignment. Be sure to begin working on this early in the week.PromptAfter completing the textbook reading and reviewing the mongoimport tool documentation in the module resources, complete the following tasks using the mongo shell in Apporto.The data set for this assignment, city_inspections.json, has already been loaded into the Apporto environment for you. Using the mongoimport tool, load the database “city” with documents found in the city_inspections.json file into the “inspections” collection. Complete this by typing the following commands in the Linux terminal to perform the import in the right directory: <code>cd /usr/local/datasets/ #change into the Apporto directory with the data sets mongoimport --db city --collection inspections ./city_inspections.json #mongo import utility </code>TIP: In any Linux systems, commands must be exact and use proper syntax and case sensitivity.Verify your load by switching to the “city” database and issuing the following queries in the mongo shell:db.inspections.find({"id" : "10021-2015-ENFO"})db.inspections.find({"result":"Out of Business"},{"business_name":1}).limit(10)Provide screenshots of the results as evidence.Using the appropriate commands in the mongo shell, insert a document to the database named “city” within the collection named “inspections.” Use the following key-value pairs as data for your document. KeyValueid“20032-2020-ACME”certificate_number9998888business_name“ACME Explosives”dateToday’s dateresult“Business Padlocked”sector“Explosive Retail Dealer-999”addressnumber -> 1721street -> Boom Roadcity -> BRONXzip -> 10463Please look at the attached picture to get a better look at the table.Be sure the address is inserted as a sub-document, and use the JavaScript function Date() for “Today’s date.” Verify your database creation and insertion using the findOne() function in the mongo shell. Provide a screenshot as evidence.Answer the following questions using MongoDB queries.What is the distinct list of inspection “sector” in the current inspections collection? How many are in the list? Do not count by hand.What is the difference in the date data type for the business named “AUSTIN 2012” versus your business document insertion of “Acme Explosives”?How many businesses have a “Violation Issued”? (See Value column above.)Verify by providing screenshots of the queries and results as evidence.Using the appropriate command in the mongo shell, update the document with the ID “20032-2020-ACME” in the collection “inspections” in the database “city” with the information below. KeyValuebusiness_name"New ACME Flowers"result"Business Re-opened"comments"Flowers after the explosion"Verify your database update using the appropriate find() function in the mongo shell. Provide a screenshot as evidence.Using the database “city” with documents found in the “inspections” collection, perform the tasks listed below. Verify by providing screenshots of the results as evidence.Update all the documents that contain the key-value pair "city":"ROSEDALE" in the address subdocument by changing the zip code in the address subdocument to "76114".Remove the first document with the key-value pair "result":"Violation Issued."Guidelines for SubmissionSubmit a Word document containing all of your screenshots. Use a screenshot tool, such as the Snipping Tool, for your screenshots and be sure to enlarge the images in the Word document before submitting. This will help make sure that your screenshots are an appropriate size for your instructor to be able to read them. Refer to this Use Snipping Tool to Capture Screenshots guide for help with taking screenshots.

Assignment Details:Think of the difference between Supervised and Unsupervised as having supervising entity letting you know if you are making the right decisions, or not in the case of supervised. The opposite would be true of unsupervised learning. Supervised learning may benefit from label classifications of data such as flowers (roses, tulips, carnations, etc.). Where unsupervised may not have a classification to benefit from as the answer to the question may be the aim.Using the provided dataset that represents the Titanic disaster, create both an unsupervised clustering algorithm to describe the data and a simple supervised classification prediction to determine who might survive. Implement your algorithms in Python. Submit 2 Python files with roughly 50-80 lines of code each and 1 MS Word document (or Jupyter Notebook).Code file must include a file header that includes the following information at a minimum: Your name, date, course, and description of the code. Code must be well-commented and in your own words. Explain your decisions and what the code is doing. Code should adhere to best practice code standards. Capture and record results and screenshots in a Word document.