Analysis on the current state of Data Professions

General Information:

Programming language used: Power BI (DAX)

Source: Kaggle

Credibility: 10/10 Kaggle scale

Hypotheses:

  1. There is near-equal gender distribution within data professions.
  2. Data science roles command significantly higher salaries compared to other data fields.
  3. Career satisfaction in data fields is influenced by salary levels and social perceptions.
  4. Python is the most popular programming language in data professions.

Process:

  • Gathered data on gender distribution, salaries, career satisfaction, and programming language preferences.
  • Performed data cleaning and normalization to ensure accuracy in analysis.
  • Utilized statistical analysis and visualizations to explore correlations and trends.
  • Developed interactive dashboards in Power BI to visualize and interpret the findings.

Findings:

  • Gender parity is nearly achieved in data professions, with 49.2% women and 50.8% men.
  • Data science roles have an average salary of $94K, approximately 30% higher than other data fields.
  • Career satisfaction scores are moderate, with a 4.27/10 rating, but there is cautious optimism for the future, reflected in a 5.61/10 score.
  • Python dominates as the preferred programming language with 66.65% usage, followed by R at 16%.

Visualization:

Created an interactive dashboard in Power BI to effectively communicate the findings, highlighting key insights and trends within the data professions.