create a mocked architecture for such a project and present its outcomes to the management team.

Assignment
1. Read the Unit Introduction.
2. Complete the assigned readings.
3. By the deadline, post the deliverables of your Mobile Analytics Architecture Project for evaluation in the unit assignment folder and in Blackboard Collaborate (slide presentation).
A well-established life sciences organization, that conducted hundreds of pre- and post-clinical studies in its long history, decided to take advantage of the current information technologies in the mobile computing domain in order to improve effectiveness and efficiency of their medical drug trials. In particular, they wanted to seek better ways of conducting their ongoing initiatives related to obesity research. The first step they took was to create a new Data Science unit in charge of data analytics, machine learning, and data integration. However, before making any sizable investments into a full-scale mobile computing program and getting “real” patients engaged, they wanted to run a hypothetical pilot to see whether their potential investment makes sense.
As a newly hired Data Architect right out of a challenging graduate program at UIC, your job on this particular assignment is to collaborate with the Information Technology infrastructure team to create a mocked architecture for such a project and present its outcomes to the management team. Since you cannot yet apply your skills with “real” patients and new devices, you are searching for data and tools to design your project on paper, in order to convince your bosses to take the next step and invest into the more advanced wave of development. You decided on the following strategy that requires no external budget to begin.
Your deliverables for this assignment are:
Word document with answers to points (1), (2), (3), and (5). Include your name and unit number on the document. Submit to assignment folder in this unit.
PDF of your architecture diagram as answer to point (4). Include your name and unit number on the document. Submit to assignment folder in this unit.
Create a Power Point presentation and save it as a PDF, to satisfy requirement (6) upload to Blackboard. Include your name and unit number on the document.
*Note 1: You are a designer starting with a clean sheet, so if it seems that there is a lot of ambiguity in this assignment, you are right, and this is the intention. This is a situation you could encounter in the job marketplace when you enter or re-enter the workforce. Successful data scientists and architects do not attempt to solve or improve existing solutions. They either resolve known big challenges or create new innovations.
*Note 2: Many examples of software and hardware architecture models can be found online, and some foundational courses in the BHIS program, such as 515 and 520, have already introduced these models and concepts. However, in this case, some considerations should be given to the following:
– How data is gathered by a mobile device and flows into and through the application
– Data flow from collection to analysis
– A diagram reflecting core parts of your architecture, and depicting how data flows between users and application subsystems. – A description and analysis of all artifacts appearing on your diagram, with a detailed explanation.
*Note 3: Please remember to cite and reference in APA, to not plagiarize, and avoid using resources representing someone’s unverified opinions such as Wikipedia and online blogs. Professional literature can be used, but carefully scrutinized for quality and reputation of the knowledge source.
see attached document for full guidline. ANSWER
What are the goals of the mobile analytics pilot project?
The goals of the mobile analytics pilot project are to:
* Determine the feasibility of using mobile devices to collect data for obesity research.
* Identify the challenges and opportunities of using mobile devices for data collection.
* Develop a prototype mobile app for collecting data on obesity.
* Test the prototype mobile app with a small group of patients.
What are the key components of the mobile analytics architecture?
The key components of the mobile analytics architecture are:
* Mobile devices: The mobile devices will be used to collect data on obesity. The devices will be equipped with sensors that can measure things like weight, height, and activity level.
* Mobile app: The mobile app will be used to collect and store data from the mobile devices. The app will also be used to transmit data to the cloud.
* Cloud: The cloud will be used to store and analyze data from the mobile devices. The cloud will also be used to develop and deploy the mobile app.
* Data analysis tools: Data analysis tools will be used to analyze data from the mobile devices. The tools will be used to identify trends and patterns in the data.
What are the data flow and security considerations for the mobile analytics architecture?
The data flow for the mobile analytics architecture is as follows:
* Data is collected by the mobile devices.
* Data is stored on the mobile devices.
* Data is transmitted from the mobile devices to the cloud.
* Data is stored in the cloud.
* Data is analyzed in the cloud.
The security considerations for the mobile analytics architecture are as follows:
* The data must be encrypted to protect it from unauthorized access.
* The data must be stored in a secure location.
* The data must be accessed only by authorized users.
What are the ethical considerations for the mobile analytics pilot project?
The ethical considerations for the mobile analytics pilot project are as follows:
* Patients must be informed about the purpose of the study and how their data will be used.
* Patients must give their consent to participate in the study.
* The data must be used only for research purposes and not for any other purpose.
* The data must be kept confidential.
What are the next steps for the mobile analytics pilot project?
The next steps for the mobile analytics pilot project are to:
* Develop a detailed plan for the pilot project.
* Recruit patients to participate in the pilot project.
* Test the prototype mobile app with the patients.
* Analyze the data collected from the pilot project.
* Evaluate the results of the pilot project.