Data Analytics Capstone Project
Timeline
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March 31, 2020Experience start
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April 2, 2020Project Scope Meeting
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April 4, 2020Final Report
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April 25, 2020Data Understanding/Data Preparation
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May 16, 2020Displaying Data using Data Analytics Tools
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May 30, 2020Gathering more value from data using Python
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June 28, 2020Experience end
Timeline
-
March 31, 2020Experience start
-
April 2, 2020Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
April 4, 2020Final Report
Following the CRISP-DM methodology, students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
April 25, 2020Data Understanding/Data Preparation
Students should generate documentation on data understanding for the data assets available, provided, or to be gathered. Documentation should also be provided on the data preparation steps utilized to prepare the data for further analysis.
-
May 16, 2020Displaying Data using Data Analytics Tools
Students should generate a data visualization example using Power BI outlining the intended/exercised data to generate insight and recommendations.
-
May 30, 2020Gathering more value from data using Python
Students will demonstrate their approach to extracting more value from their data using Python for data analysis.
-
June 13, 2020Managing Data in the Cloud
Students will demonstrate ways to manage data in the cloud using MS Azure as a platform, and provide recommendations on cloud solutions.
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June 27, 2020Final Report/Demonstration
Students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
June 28, 2020Experience end
Experience scope
Categories
Information technology Data analysisSkills
business analytics business consulting data analytics storytelling and data visualization data analysisAre you a firm that is looking to explore the value of data analytics? Students in the SAIT Data Analytics certificate are trained in data extraction and transformation, data preparation, data modelling and reporting on pre-existing data gathered by the organization. These students will work with your organization to analyze your data sets and provide any recommendations they may have as a result of the analysis.
Please note: EDGE UP courses give preference to companies located in Calgary.
Learners
The final project deliverable will include:
- A 10 to 20-page report outlining the work they performed, any analysis they conducted including visualizations and any recommendations they may have as a result of analysis.
- A 20-minute presentation of the project and results to the industry partner and classmates.
Project timeline
-
March 31, 2020Experience start
-
April 2, 2020Project Scope Meeting
-
April 4, 2020Final Report
-
April 25, 2020Data Understanding/Data Preparation
-
May 16, 2020Displaying Data using Data Analytics Tools
-
May 30, 2020Gathering more value from data using Python
-
June 28, 2020Experience end
Timeline
-
March 31, 2020Experience start
-
April 2, 2020Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
April 4, 2020Final Report
Following the CRISP-DM methodology, students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
April 25, 2020Data Understanding/Data Preparation
Students should generate documentation on data understanding for the data assets available, provided, or to be gathered. Documentation should also be provided on the data preparation steps utilized to prepare the data for further analysis.
-
May 16, 2020Displaying Data using Data Analytics Tools
Students should generate a data visualization example using Power BI outlining the intended/exercised data to generate insight and recommendations.
-
May 30, 2020Gathering more value from data using Python
Students will demonstrate their approach to extracting more value from their data using Python for data analysis.
-
June 13, 2020Managing Data in the Cloud
Students will demonstrate ways to manage data in the cloud using MS Azure as a platform, and provide recommendations on cloud solutions.
-
June 27, 2020Final Report/Demonstration
Students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
June 28, 2020Experience end
Project Examples
Requirements
Beginning in April, students in groups of 2-4 will spend 102 hours assisting your company by providing analytical research and recommendations tailored to one of your company’s data opportunities or challenges.
Students will develop the following skills and competencies and will develop the knowledge, skills, and aptitude to apply fundamental principles of data analytics to support business decision-making processes, creating accurate and meaningful storytelling with actionable insights. They will accomplish this using a foundation of data management and ethics.
Program Outcomes
- Understand database concepts, how to design and implement databases to maintain data integrity
- Develop skills to query data using SQL scripting
- Manipulate data using ETL principles (extract, transform, load) to develop a data repository that can then be analyzed in a business context that is relevant to decision-making
- Apply fundamental data analytics principles, aligning data and business processes to create accurate, actionable insights
- Use industry recognized programs and tools to extract meaning from data (Cognos, Power BI)
- Present data that communicate data analysis effectively and accurately for a business audience using visualizations (dashboards) and reports
- Develop skills in Python programming, specific to data analysis functions
- Introduce cloud principles for managing data in the cloud, using Microsoft Azure as the platform
Students may work with the company in one of three ways:
- Assist organizations in data gathering research and/or prepare data for future use by the organization. Students can help design and model databases to gather and store data for future analysis
- Assist organizations in preparing existing data for analysis. Students may perform data quality checks, data cleaning, and data transformation exercises on existing data to ready data for analysis by the organization
- Assist organizations in data analysis. Using organizational data, students may conduct data analysis and design data analytics reports to be delivered to the firm
Project examples include but are not limited to:
- Analysis of customer segmentation relative to different products and services, to enhance marketing campaigns and refocus your products/services
- Investigate predictive models to understand trends in sales, attrition rates, and profits that impact your business
- Propose new ways to visualize data through tables and plots that can provide new insights for managers
Participating industry partners provide data sets.
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
Be available for a quick phone call with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the course.
Provide a dedicated contact who is available to answer periodic emails or phone calls over the duration of the project to address students' questions.
Provide data sets for students to analyze
Timeline
-
March 31, 2020Experience start
-
April 2, 2020Project Scope Meeting
-
April 4, 2020Final Report
-
April 25, 2020Data Understanding/Data Preparation
-
May 16, 2020Displaying Data using Data Analytics Tools
-
May 30, 2020Gathering more value from data using Python
-
June 28, 2020Experience end
Timeline
-
March 31, 2020Experience start
-
April 2, 2020Project Scope Meeting
Meeting between students and company to confirm: project scope, communication styles, and important dates.
-
April 4, 2020Final Report
Following the CRISP-DM methodology, students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
April 25, 2020Data Understanding/Data Preparation
Students should generate documentation on data understanding for the data assets available, provided, or to be gathered. Documentation should also be provided on the data preparation steps utilized to prepare the data for further analysis.
-
May 16, 2020Displaying Data using Data Analytics Tools
Students should generate a data visualization example using Power BI outlining the intended/exercised data to generate insight and recommendations.
-
May 30, 2020Gathering more value from data using Python
Students will demonstrate their approach to extracting more value from their data using Python for data analysis.
-
June 13, 2020Managing Data in the Cloud
Students will demonstrate ways to manage data in the cloud using MS Azure as a platform, and provide recommendations on cloud solutions.
-
June 27, 2020Final Report/Demonstration
Students should generate documentation on the evaluation of the model and results, along with the outcomes of deployment of the model on production data. Any presentation materials and generated reports should be ready for presentation.
-
June 28, 2020Experience end