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BUILDING AN HNG HIRE DATA MODEL AND HIRING STATISTICS DASHBOARD

Table of contents

About

The project involves creating a data model for HNG Hire, implementing it in MySQL, and building a Power BI dashboard to display hiring statistics.

Project Overview

Prepare a data model for HNG Hire, implement it in MySQL, and then build a dashboard that shows hiring statistics. Show available people per stack, those in interviews, those who are hired, etc. Think through all the things that should be tracked for the model. Write some useful filters on the data.

Business Requirements

HNG Hire aims to match talent with opportunities by helping employers find the right candidates for their roles. For this project, we need to track:

  • Candidates: Basic details, technology stacks, status in the hiring process (available, in interview, hired, etc.)
  • Hiring Process: Details about interviews, offers, rejections, etc.
  • Employers: Information about companies that are hiring, the roles they are offering, etc.

Data Model Design

A Multi-Dimensional data model (star schema) was utilized in designing the HNG hire data model, with a hiring fact table and seven dimension tables (candidates, employers, job roles, stack, status, location, date).

Fact Table:

hiring

Column Name Data Type Description
hiring_id Integer Primary key
candidate_id Integer Foreign key to candidates
employer_id Integer Foreign key to employers
job_role_id Integer Foreign key to job roles
stack_id Integer Foreign key to stack
status_id Integer Foreign key to status
date_id Integer Foreign key to date
location_id Integer Foreign key to location
interview_score Float Interview score
years_of_experience Integer Years of experience of the candidate

Dimension Tables:

candidates

Column Name Data Type Description
candidate_id Integer Primary key
full_name Varchar Candidate's full name
email Varchar Candidate's email address
phone_number Varchar Candidate's phone number
github_profile Varchar Candidate's GitHub profile URL
linkedin_profile Varchar Candidate's LinkedIn profile URL
experience_level Varchar Candidate's experience level (Junior, Mid, Senior, etc.)

employers

Column Name Data Type Description
employer_id Integer Primary key
company_name Varchar Name of the hiring company
industry Varchar Industry of the company
location Varchar Location of the company

job_roles

Column Name Data Type Description
job_role_id Integer Primary key
job_title Varchar Title of the job role (e.g., Data Analyst, Frontend Developer)
description Text Description of the job role

stack

Column Name Data Type Description
stack_id Integer Primary key
stack_name Varchar Name of the technology stack (Frontend, Backend, Mobile, etc.)

status

Column Name Data Type Description
status_id Integer Primary key
status_name Varchar Name of the status (Available, In Interview, Hired, Rejected)

location

Column Name Data Type Description
location_id Integer Primary key
country Varchar Country of the location
city Varchar City of the location

date

Column Name Data Type Description
date_id Integer Primary key
full_date Date Complete date (YYYY-MM-DD)
year Integer Year of the date
month Integer Month of the date
day Integer Day of the month
quarter Integer Quarter of the year
is_weekend Boolean Indicates if the date is a weekend
interview_date Date Date of the interview (if applicable)
hiring_date Date Date of hiring (if applicable)

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Data Loading

Dummy data was randomly created and loaded into each of the tables in the hng_hire database on MySQL

Fact table data

Dimension table data

Links

Key Insights

Here are the key insights from the report:

  • Candidate Distribution: There are a total of 6 candidates in the HNG hire pool.
  • Hiring Status: 33% of candidates are currently being interviewed, 33% are available for a job, and 33% have been hired.
  • Role Distribution: 1 Frontend Designer and 1 UX Designer have been hired; 1 Data Analyst and 1 DevOps Engineer are currently being interviewed.
  • Stack Representation: Each technology stack has just 1 candidate in the HNG hire candidate pool.

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Acknowledgements

This project is part 3 of three tasks required to graduate from Stage 8 at HNG 11 internship for the Data Analyst Track. Special appreciation to the organizers of the internship, and to my esteemed team members in team Bulldozer - Blessing Laweh, Adesola Ogundipe, Abena Agyemang Gyasi, Omolola Alonge - who together we made it as HNG Finalist in the data analyst track.