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Capstone course in Business Insights and Analytics

BIA 5450
Closed
Humber College
Humber College
Toronto, Ontario, Canada
Nataliya Korchagina
Nataliya Korchagina
Program Coordinator/Professor
(2)
3
Timeline
  • March 14, 2022
    Experience start
  • April 23, 2022
    Project Scope Meeting
  • May 23, 2022
    Stage 1
  • June 6, 2022
    Stage 2
  • June 20, 2022
    Stage 3
  • August 20, 2022
    Stage 4
  • August 20, 2022
    Experience end
Experience
5 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any
Any industries
Categories
Information technology Data analysis Market research
Skills
business analytics data analysis research
Learner goals and capabilities

Are you looking for ways to monetize your data more effectively? Does your business have lots of historical data requiring cleaning and profiling? Are you interested in merging your internal data to various external data to derive new business insights? Do you face a specific business problem that can be tackled by using advanced statistical analysis, databases, big data, and machine learning tools? Business Insights and Analytics Post-Graduate Certificate Program at Humber College can help you find solutions to these problems. How? Partner with us in a Capstone project and benefit from getting a team of 5-6 students supervised by an experienced professional who will help you come up with a data-driven solution. The team will help you define the scope of the problem and the data for further analysis. They will apply a broad range of data analytics skills to build a solution and present business insights for your consideration.

Learners
Post-graduate
Any level
30 learners
Project
120 hours per learner
Learners self-assign
Teams of 6
Expected outcomes and deliverables

Our students are:

- Well-versed in application of legislative requirements related to data protection

- Able to ask analytical questions, formulate a problem and define required data entities

- Able to profile data & conduct statistical analysis to assess data quality

- Able to use UML diagram to represent a business problem solution

- Able to uncover unidentified relationships between data

- Able to organize multiple data sources into an enterprise-wide database using SQL

- Able to develop descriptive/diagnostic/predictive/prescriptive models (i.e., Java, SPSS, SPSS Modeler, SAS, Python) to help managers derive business insights

- Able to manipulate & merge any type of data (structured, semi structured, unstructured) & use R for Big Data manipulation

- Skilled at working with the Hadoop architecture & querying large amounts of data using Map Reduce

- Able to define what dashboards are needed in a specific situation & identify the ideal visual to present data (i.e., Excel, Tableau, Power BI)

- Able to simulate/test the solution to a problem, conduct UAT, & integrate feedback.

Expected deliverables by the end of the project:

- Data analytics-base solutions (i.e., statistical analysis, dashboards, predictive model, machine learning implementation, etc.)

- The results will be communicated in a final presentation and final report.

Project timeline
  • March 14, 2022
    Experience start
  • April 23, 2022
    Project Scope Meeting
  • May 23, 2022
    Stage 1
  • June 6, 2022
    Stage 2
  • June 20, 2022
    Stage 3
  • August 20, 2022
    Stage 4
  • August 20, 2022
    Experience end
Project Examples

Examples of the problems that we will help you solve in different functions/areas are:

In sales

· Identify cross-selling opportunities based on customer purchase history to enhance sales and improve customer experience

· Increase sales by identifying seasonal trends

· Identify profitable vs. unprofitable customers

· Predict the likelihood of customer attrition

· Determine which items should be on sale and avoid having an item and its complimentary (example: pasta and sauce) on sale at the same time

In supply chain

· Determine how much inventory to have at a given time to manage costs and space effectively

· Evaluate the efficiency of current suppliers and predict that of potential suppliers

In marketing

· Identify customer segments and select the best product/service to bring to the market

· Improve marketing campaigns based on the sentiment analysis

In finance

· Identify which bank client has a higher probability to apply for a mortgage

· Identify which clients will most likely not pay their mortgage/loan/debt

· Determine the credit limit a bank/financial institution can offer to a clientExamp

In HR:

· Determine which employee is more likely to leave the company and why

· Determine whether a potential applicant fit the company

Companies must answer the following questions to submit a match request to this experience:

Provide feedback on the project progress and final solution - estimated 15-20 hours’ time commitment.

Be available for initial meetings with the Capstone faculty/mentors to initiate your relationship and confirm your scope is an appropriate fit for the course. Provide project scope, a mix of internal data and tips for external data sources.

If your project requires specific software, you will need to provide access to it. (Our students will be equipped with access to a broad range of the software used in the program (i.e., SSMS and SQL Server, IBM SPSS Statistics, Python with numpy and matplotlib libraries, SAS Studio, SAS Enterprise Miner, IBM Cognos Analytics, IBM Watson Studio, IBM Cloud Services, Tableau, R Studio, Neo4j database system, Power BI, etc.)).

Provide a dedicated contact who is available to answer periodic emails or phone calls over the duration of the project to address students' questions. Checking in with students as the project progresses with regular meetings, reviews, and updates.