Data Analyst Application Data. EDA
How will knowing top hiring data job titles help your job search as a Data Analyst?
It’s a no brainer a lot of people are learning and entering into the data field, with facts showing most people learning to be a Data Analyst, which invariably makes Entry Level Data Analyst job search space more than saturated, to say the least, an Entry Level Data Analyst, looking for a job in the same saturated space made me interested in analyzing the data, and showcase my skill of performing a complete project on Excel.
I downloaded the data from Google Data Analytics Certificate Hands-on Activity. It’s 32,596 data analyst job application data across 19 states in the US in the year 2019. The dataset contains applicants applied job title, job location, application date-time, and survey that return Boolean TRUE or FALSE to these questions;
- Is the application process easy or not?
- Applicant hired or not?
I performed all data cleaning, preparation, analysis, and visualization using Excel, created pivot tables to organize, analyze data, and choose the right pivot tables to make visualization in line with the data story being told.
All the pivot tables that make up the visuals, as well as my data cleaning report, are provided below.
Some of the business questions to be answered?
· What are trends in how people apply? and got hired? Or not hired?
· What percent of applicants find the application easy?
· What percent of easy applicants got hired?
· What’s the most applied job title? And which job title hired the most?
· Which job location hires the most applicants?
Data Cleaning ChangeLog
Date: 10/11/2022
Dataset: 2019 Data Analyst Job Application Data
# Changes
· Used Text to Column to split the date-time in column B into separate columns of date and time, then deleted the time column as there’s no need for it.
· Implemented the RIGHT function to extract the two letters abbreviation for STATE from the Job Location column to a new column tagged STATE.
# Fixes
· Formatted the date from the Text to Column action above to the needed short date format.
# Addition
· Used TEXT function to extract Month as text from the short date formatted column, into a new column named MONTH for ease of processing.
Data Cleaning Report
· I used the LEN function to validate the length of the applicant ID, as it’s supposed to be of fixed length.
· I used the TRIM function to remove any space before, between, and after all the Text data.
· Checked spelling errors since we have a lot of strings in the dataset.
· Checked to make sure both (Easy Apply and Hired) columns with TRUE or FALSE Boolean values are consistent through all records.
· Created 2 new columns STATE AND MONTH.
· Checked for duplicates to avoid duplicate values that can skew our analysis.
The Data cleaning leaves us with 8 columns of 32,596 records of clean and accurate data to prepare for analysis.
Data Analysis / Pivot Tables
Trends in the monthly application? Hire? Not hired?
Easy Apply Summary
Hiring Summary
Which Job title is hiring the most?
What percentage of Easy Apply got hired?
Top 3 most applied job titles and 2 least applied job titles
Top 5 hiring Job titles (in terms of applicants per job)
Data Visualisation
As industries’ need for Data Analyst increases, different industries are putting out Job Openings with job titles that resonate with what purpose Data Analyst will serve in the organization, which are out of the conventional Business Data Analyst title, so Data Analysts looking for a job can apply those not so popular Job titles.
Though we don’t know the total number of Data job openings across the states for the year in review, it’s a no-brainer that multiple applications will come for each job opening, also different Data Analyst applies across different job openings, nevertheless, as observed the percentage of applicants that finds the application process difficult hard is high, coupled with the fact that all applications under the 2 job titles that none got hired didn’t find application process easy.
Further surveys need to be done to ask more specific, relevant, action-oriented questions on why applicants find the application process not easy.
Thanks for reading.
