This repository contains a collection of synthetic data files, created as a case study for the purpose of hiring new analytics team members at Canadian Shield Healthcare Services. Please note that all data provided here is entirely fictional and has been generated for educational and evaluative purposes only.

• File: Clients.json
• Content: Includes detailed information about clients such as IDs, status, full names, birth dates, gender, marital status, medical conditions, city, zip codes, and group IDs.
• Usage: Ideal for analyzing client demographics and medical condition prevalence.

• File: Employee.json
• Content: Contains data on employees including IDs, full names, birthdays, genders, marital statuses, statuses in Canada, cities, hire and termination dates, employment types, job titles, and current status.
• Purpose: Useful for workforce analytics and employment trends study.

• File: Groups.json
• Content: Lists groups within Canadian Shield Healthcare Services, each with a unique ID and name.
• Application: Can be used for analyzing organizational structure and group distribution.

• Files:
  • Visits 2020 Q1
  • Visits 2020 Q2
  • Visits 2020 Q3
  • Visits 2020 Q4
  • Visits 2021 Q1
  • Visits 2021 Q2
  • Visits 2021 Q3
  • Visits 2021 Q4
  • Visits 2022 Q1
  • Visits 2022 Q2
  • Visits 2022 Q3
  • Visits 2022 Q4
• Content: Detailed records of visits for each quarter from 2020 to 2022, including timings, service codes, employee-client interactions, etc.
• Purpose: Key for analyzing service delivery patterns, visit frequencies, and operational insights.

Prospective analytics team members are encouraged to utilize this dataset for demonstrating their skills in data manipulation, analysis, and visualization. The data represents a simulated real-world scenario in the healthcare services sector. Please refer to the specific instructions you will receive for the position you are applying for.

It is important to reiterate that the data in this repository is entirely fictitious and created for this case study. It should be treated with the same level of confidentiality and ethical consideration as real-world healthcare data.