In a world where efficiency and precision are paramount, connecting candidates with the right job opportunities hinges on effective distance management. We are excited to introduce our latest tool – the Distance Matrix Dashboard. This powerful resource simplifies the process of matching candidates with job openings by providing crucial insights into commute times and distances.
Introduction
The \”Eye to Eye\” project aimed to analyze and process data from the \”Eye to Eye\” PostgreSQL database. The objective was to clean the data and perform a join operation between job and candidate information based on the state. This project successfully achieved its goals by extracting relevant data, obtaining latitude and longitude coordinates using geocoding APIs, calculating distance and travel time between locations, and storing the data in a PostgreSQL database.
And then creating a dashboard in PowerBI.
Data Extraction and Cleaning
The initial phase of the project involved extracting data from the \”Eye to Eye\” PostgreSQL database. The extracted data contained information about jobs and candidates. To ensure a distinct entry for each job and candidate in the same state, a cleaning process was performed.
Geocoding and Distance Calculation
To determine the distance and travel time between candidate and job locations, the project initially utilized the Google Geocoding API. By obtaining the latitude and longitude coordinates of candidate and job zip codes, the project could accurately calculate distances. However, it was discovered that the cost associated with the Google Geocoding API was prohibitively high, leading to a change in approach.
Transition to NextBillion.ai
Due to the cost constraints of the Google Geocoding API, the project transitioned to using NextBillion.ai\’s geocoding and distance matrix services. However, NextBillion.ai provided inaccurate latitude and longitude values for certain zip codes outside of the USA. Consequently, the project decided to retrieve data for the USA.
Data Extraction and Storage
After resolving the geocoding challenges, the project successfully extracted the data in CSV format. To facilitate data management and future operations, the project imported the extracted data into a PostgreSQL database.
Data Refresh Mechanism
A data refresh mechanism was implemented to keep the information up to date. Initially, an approach based on storing the ID of the last candidate and job was adopted. However, this approach proved flawed, as new entries did not always follow the expected ID behavior. Moreover, some candidates were missing from the data as there were no corresponding jobs. To address these issues, an alternative refresh mechanism was designed. This mechanism involved performing a join operation between the existing data and the \”Eye to Eye\” data, identifying new candidates and jobs, and integrating them into the dataset.
Navigating Distance with Precision
Imagine having a single dashboard that effortlessly calculates commute times and distances between candidates and job locations. The Distance Matrix Dashboard does just that and more.
Key Performance Indicators (KPIs)
This dynamic dashboard offers a comprehensive set of KPIs, enabling you to optimize candidate placement and job matching:
Total Jobs: Keep track of the number of job openings.
Candidate Name: Identify candidates for potential job placements.
Candidate Address: Obtain candidate location details.
Job Distance: Calculate the distance between candidates and job locations.
Commute Time: Determine the time required for candidates to reach job locations.
Job Title: Understand the nature of job openings.
Job Address: Obtain job location details.
Jobs Title by Commute Time and Distance: Analyze job titles based on commute times and distances.
Location of Candidate and Job: Visualize candidate and job locations on a map.
Table View: Get a detailed view of job titles, cities, commute times, and distances in miles.
Empowering Informed Job Matching
The Distance Matrix Dashboard empowers organizations to make data-driven decisions when it comes to candidate placement and job matching. Here\’s how it works:
Total Jobs: Assess the volume of job opportunities available.
Candidate Name and Candidate Address: Gain insight into candidate profiles and locations.
Job Distance and Commute Time: Optimize job matching based on proximity.
Job Title and Job Address: Understand the specifics of job openings.
Jobs Title by Commute Time and Distance: Match candidates with jobs based on their preferences and practicality.
Location of Candidate and Job: Visualize candidate and job distribution for strategic decisions.
Table View: Delve into detailed job listings, commute times, and distances.
Efficiency in Job Matching
The Distance Matrix Dashboard serves as your compass, guiding you through the intricacies of candidate placement and job matching. Whether you\’re a talent acquisition manager, HR professional, or a business leader, this tool equips you with the insights needed to streamline candidate placements and improve efficiency.
Conclusion
In a world where the right job placement can change lives, the Distance Matrix Dashboard becomes your strategic ally. It simplifies the job matching process, empowers data-driven decisions, and ultimately connects candidates with their ideal job opportunities.
Stay tuned for more updates and insights from our suite of data analysis tools. The future of efficient job placement is here, and data power it.
