Using ChatGPT to analyze government data, looking for interesting trends or information.
Date of Analysis: 9 May 2024 (Data 21 March 2022 through 22 April 2024)
Total Data Rows The total number of data rows in the dataset is 973 rows (edited).
5-Number Summary for the Number of Individuals Affected by Breaches
Minimum: 500
1st Quartile (Q1): 981
Median: 40000
3rd Quartile (Q3): 17964
Maximum: 11270000
Statistical Summary of Breach Types
Type of Breach: All 973 breaches are categorized as “Hacking/IT Incident.”
Percentage of Individuals Impacted by the Type of Breach:
“Hacking/IT Incident” accounted for 100% of the breaches, impacting a total of 51,105,267 individuals.
Statistical Summary of Location of Breached Information (Top 10 States by Location of Breached Information)
California (CA)
Total individuals impacted: 19,484,442
Percentage of total: 38.1%
Texas (TX)
Total individuals impacted: 5,780,247
Percentage of total: 11.3%
Illinois (IL)
Total individuals impacted: 4,174,737
Percentage of total: 8.2%
Colorado (CO)
Total individuals impacted: 13,215,262
Percentage of total: 25.9%
Florida (FL)
Total individuals impacted: 10,739,234
Percentage of total: 21.0%
Virginia (VA)
Total individuals impacted: 10,000,000
Percentage of total: 19.5%
Arizona (AZ)
Total individuals impacted: 10,000,000
Percentage of total: 19.5%
Georgia (GA)
Total individuals impacted: 3,605,858
Percentage of total: 7.1%
North Carolina (NC)
Total individuals impacted: 3,520,394
Percentage of total: 6.9%
Washington (WA)
Total individuals impacted: 1,902,589
Percentage of total: 3.7%
Comprehensive Statistical Summary of Individuals Affected by State
Top Three Most Affected States
California (CA)
Total individuals impacted: 19,484,442
Percentage of total: 38.1%
Colorado (CO)
Total individuals impacted: 13,215,262
Percentage of total: 25.9%
Texas (TX)
Total individuals impacted: 5,780,247
Percentage of total: 11.3%
Bottom Three Least Affected States
Nebraska (NE)
Total individuals impacted: 149,019
Percentage of total: 0.29%
Vermont (VT)
Total individuals impacted: 126,819
Percentage of total: 0.25%
Utah (UT)
Total individuals impacted: 126,819
Percentage of total: 0.25%
Analysis of Breach Submission Date by Month (Total Occurrences and Percentage)
January 2024
Total occurrences: 118
Percentage of total: 12.1%
February 2024
Total occurrences: 112
Percentage of total: 11.5%
March 2024
Total occurrences: 121
Percentage of total: 12.4%
April 2024
Total occurrences: 137
Percentage of total: 14.1%
May 2024
Total occurrences: 30
Percentage of total: 3.1%
June 2023
Total occurrences: 104
Percentage of total: 10.7%
July 2023
Total occurrences: 68
Percentage of total: 7.0%
August 2023
Total occurrences: 66
Percentage of total: 6.8%
September 2023
Total occurrences: 75
Percentage of total: 7.7%
October 2023
Total occurrences: 73
Percentage of total: 7.5%
November 2023
Total occurrences: 68
Percentage of total: 7.0%
December 2023
Total occurrences: 41
Percentage of total: 4.2%
Insights into Seasonality and Reporting Trends
Peak Months:
The peak months for breach submission were March and April, which could be attributed to organizations closing their fiscal year, audit reports, or regulatory compliance. Increased cybersecurity risks during these periods might lead to a higher number of reported breaches.
Lowest Months:
The least prevalent months for breach submission were May (partial month), July, and August. This could be due to summer vacation schedules, leading to slower reporting rates.
Seasonal Influences:
The data suggest that there might be seasonal trends, with higher breach reports during fiscal year-end, regulatory compliance, and tax season. Summer months tend to be lower, possibly due to holiday schedules.
The ChatGPT Prompt Used:
In a moment, I’m going to give you some data about people’s PII data that was breached.
Please only use the last 12 months of data and today’s date is 9 May 2024. Please title the dataset 12 months of OCR Data Breach Data. Please provide the total number of data rows in the data set. Also, please provide a 5-number summary for the number of individuals affected by breaches. Please make sure all of your analysis for possible reasons of the data is cohesive and comprehensive. Please provide a comprehensive statistical summary of breach types by type and the percentage of individuals impacted by the type of breach. Please provide a comprehensive statistical summary of the location of breached information by location of breached information, giving the ranking and percentage of the total for the top 10 states. Please provide a comprehensive statistical summary of the individuals affected by state. Please provide the top three most affected states with their total number of individual affected and the percentage of the total number of individuals in the last year impacted. Please provide a comprehensive statistical summary of the individuals affected by state, giving the bottom three most affected states with their total number of individuals affected and the percentage of the total number of individuals in the last year impacted. I hypothesize that there are broad seasonal trends, so using a breach submission date and a likely skew of up to 60 days as allowed by the reporting entity. Please provide a comprehensive analysis of the Breach Submission Date and analyze by month for the most prevalent months and least prevalent months over the last year. As part of the Breach Submission Date analysis please give the total number of occurrences by month, and the percentage of times in total the month is represented. Please provide based on the Breach Submission Date a list and analysis of possible reasons like school, business trends and seasonality of reporting of information to regulators for any seasonality to breaches. Please examine the peak months and when they occur during the year for insights into why those particular months might be important. Similarly, examine the lowest months (removing the last month of data because it is a partial month) for insights into why those particular months might not be represented so highly. Here is the data.
Comment: I’ll let some of you wonder why I use the word please so often. It is not just to be polite, and it is purposeful.
Data Source: ttps://ocrportal.hhs.gov/ocr/breach/breach_report.jsf
