Description
CEIS 110 Final Course Project
Course Project
DeVry University
College of Engineering and Information Sciences
Course Number: CEIS110
Background
Data generated from a variety of sources is growing exponentially. For example, one autonomous car can generate as much as 4000 GB of data per day. IoT sensors, mobile devices, social media, and websites generate large amounts of data requiring storage, management, analysis, and security. Large datasets or big data can be analyzed and turned into information to assist companies with decision making.
This course project covers data analysis using Python and is divided into six parts. Each week builds upon the project resulting in an analysis of weather data downloaded from a cloud data source, stored in a database, extracted and processed. The design and development process of the system will include planning, software setup, programming, and data analysis. It will encompass the many aspects of the software development process and prepare you for your future career in technology.
Expectations for Final Deliverable
To submit your final project, assemble all of your previous project submissions into one professionally designed presentation. Review your previous module submissions and enhance any areas that could be improved when compiling the final project. The presentation should explain your project in detail and illustrate to any employer your competence as a technology expert.
From each module’s submissions, include all screenshots, pictures, and explanation slides. In addition, develop slides to transition and explain each stage of the development process and customize your presentation to reflect a professional appearance. You will also need an introduction slide, conclusion slide, and challenges in the project slide, and career skills obtained slide. You should have around 28 – 35 slides.
Final Submission:After you develop your final project presentation, upload your final project to your Wix site. If you have not created a Wix site yet, please view the Wix Site Set-up Instructions to set up your free Wix.com account. Next, submit your final project through the Assignments page, and also copy the link from your published Wix site and include the link in the comments when you submit your final presentation though the Assignments page. Once you upload this and other projects to Wix.com, you can showcase your projects to potential employers. This is a great way to demonstrate the skill you have obtained from the projects. Refer to the grading rubric below to ensure you incorporate the essential elements into your project.
CEIS110 Final Project Rubric
| Criteria | Ratings | Pts | ||||
| This criterion is linked to a Learning Outcome Analyze results of tests and experimentation. | 5.0 pts | 4.0 pts | 3.0 pts | 2.0 pts | 0.0 pts | 5.0 pts |
| threshold: 4.0 pts | Spreadsheet was developed based on formatted data from python. Chart was created from the spreadsheet. | Spreadsheet was developed based on formatted data from python. No chart was created. | CSV file was developed based on formatted data from python and not saved as a spreadsheet. Chart was created from the spreadsheet. | CSV file was developed based on formatted data from python and not saved as a spreadsheet. No chart was created. | No file was created. | |
| This criterion is linked to a Learning OutcomeBuild an IoT system utilizing principles of technology. | 30.0 pts | 25.0 pts | 20.0 pts | 15.0 pts | 0.0 pts | 30.0 pts |
| threshold: 25.0 pts | Project was built using principles of technology with no errors. The following screenshots were included: 1. Install software (anaconda/spyder for python, Excel, SQLiteStudio). 2. Running code to gather temperature and humidity data (BuildWeatherDb screenshot). 3. Use SQLiteStudio to view data in database. Screenshot of query results. 4. Use python to cleanse data (Excel spreadsheet and chart). 5. Develop plots based on data (screenshots and code). | Project was built using principles of technology with minimal errors.4 of 5 screenshots present 1. Install software (anaconda/spyder for python, Excel, SQLiteStudio). 2. Running code to gather temperature and humidity data (BuildWeatherDb screenshot). 3. Use SQLiteStudio to view data in database. Screenshot of query results. 4. Use python to cleanse data (Excel spreadsheet and chart). 5. Develop plots based on data (screenshots and code). | Project was built using principles of technology with occasional errors.3 of 5 screenshots present 1. Install software (anaconda/spyder for python, Excel, SQLiteStudio). 2. Running code to gather temperature and humidity data (BuildWeatherDb screenshot). 3. Use SQLiteStudio to view data in database. Screenshot of query results. 4. Use python to cleanse data (Excel spreadsheet and chart). 5. Develop plots based on data (screenshots and code). | Project was built using principles of technology with frequent errors. 2 of 5 screenshots present 1. Install software (anaconda/spyder for python, Excel, SQLiteStudio). 2. Running code to gather temperature and humidity data (BuildWeatherDb screenshot). 3. Use SQLiteStudio to view data in database. Screenshot of query results. 4. Use python to cleanse data (Excel spreadsheet and chart). 5. Develop plots based on data (screenshots and code). | No (0%) project was built using principles of technology. | |
| This criterion is linked to a Learning OutcomeDemonstrate communication skills in various environments and contexts. | 10.0 pts | 8.0 pts | 6.0 pts | 4.0 pts | 0.0 pts | 10.0 pts |
| threshold: 8.0 pts | Title slide, Introduction slide, challenges in the project slide, career skills slide, slides describing each module, and conclusion slide present. | Title slide, Introduction slide, slides describing each module, and conclusion slide present. | Title slide, Introduction slide, and conclusion slide present. | Title slide present. | No slides present. | |
| This criterion is linked to a Learning OutcomeDifferentiate alternative solutions to problems. | 5.0 pts | 4.0 pts | 3.0 pts | 2.0 pts | 0.0 pts | 5.0 pts |
| threshold: 4.0 pts | Data analytics question was analyzed with clearly labeled plot and explanation. | Data analytics question was analyzed with clearly labeled plot and no explanation. | Data analytics question was analyzed with poorly labeled plot. | Data analytics question was analyzed with explanation only. | No question was analyzed. | |
| This criterion is linked to a Learning OutcomeInterpret and explain the results of tests and experimentation | 10.0 pts | 8.0 pts | 6.0 pts | 4.0 pts | 0.0 pts | 10.0 pts |
| threshold: 8.0 pts | At least two plots were developed using python data analytics modules. Plots were labeled and code was included. | At least two plots were developed using python data analytics modules. Plots were labeled and no code was included. | One plot was developed using python data analytics modules. Plot was labeled and code was included. | One plot was developed using python data analytics modules. Plot was not labeled and no code was included. | No plots were created. | |
| This criterion is linked to a Learning OutcomePerform various system tests and experimentation. | 10.0 pts | 8.0 pts | 6.0 pts | 4.0 pts | 0.0 pts | 10.0 pts |
| threshold: 8.0 pts | BuildWeatherDb program was correctly implemented with data downloaded from cloud and stored in database. Screenshot of code present in deliverable and Python console screenshot showing correctly populated database. | BuildWeatherDB program was correctly implemented with data downloaded from cloud and stored in database. Screenshot present in deliverable, but missing Python console screenshot or code screenshot. | BuildWeatherDb program was implemented. Program did not work, but explanation was present. | BuildWeatherDb program was implemented. Program did not work and no explanation was present. | No program was implemented and screenshot not present. | |
| This criterion is linked to a Learning OutcomeRead and understand various types and forms of communication. | 5.0 pts | 4.0 pts | 3.0 pts | 2.0 pts | 0.0 pts | 5.0 pts |
| threshold: 4.0 pts | Flowchart was created electronically (Word, Visio, draw.io, etc) with at least 6 shapes and all shapes are labeled appropriately. Flowchart is present in deliverable. | Flowchart was created electronically (Word, Visio, draw.io, etc) with at least 6 shapes without labels. Flowchart is present in deliverable. | Flowchart was created electronically (Word, Visio, draw.io, etc) with less than 6 shapes. Flowchart is present in deliverable. | Flowchart was created in any format and is present in deliverable | No flowchart was created. | |
| This criterion is linked to a Learning OutcomeSolve unknown problems utilizing mathematical and scientific methods, software, and or equipment. | 5.0 pts | 4.0 pts | 3.0 pts | 2.0 pts | 0.0 pts | 5.0 pts |
| threshold: 4.0 pts | Error-free and commented code was developed to create a plot to analyze data. | Error-free code was developed to create a plot to analyze data. | Commented code was developed to create a plot, but contained errors. | Code was developed, but contained errors. | No code was developed. | |
| This criterion is linked to a Learning OutcomeSubmit deliverables on schedule. | 10.0 pts | 8.0 pts | 6.0 pts | 4.0 pts | 0.0 pts | 10.0 pts |
| threshold: 8.0 pts | All (100%) deliverables were submitted on schedule including link to portfolio and professional design. | All (100%) deliverables were submitted on schedule with no link to portfolio and professional design. | All deliverables were submitted on schedule with no link to portfolio and professional design. | All deliverables were submitted on schedule with no link to portfolio and poor design. | No (0%) deliverables were submitted on schedule. | |
| This criterion is linked to a Learning OutcomeTest an IoT system utilizing principles of technology. | 10.0 pts | 8.0 pts | 6.0 pts | 4.0 pts | 0.0 pts | 10.0 pts |
| threshold: 8.0 pts | Project was tested using principles of technology with no errors. 1. SQL commands execute with no errors. 2. Python code compiles and runs with no errors. Explanation was present in deliverable. | Project was tested using principles of technology. 1. SQL commands execute with no errors. 2. Python code compiles and runs with no errors. Explanation was not present in deliverable. | Project was tested using principles of technology. 1. SQL commands execute with no errors. 2. Python code did not work as expected. Explanation was present in deliverable. | Project was tested using principles of technology. 1. SQL commands did not execute. 2. Python code did not work as expected. | Project was not tested using principles of technology. | |