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Why Is Analyzing Data on Divorced Women Over 45 Crucial for Government Policy-Making?
Understand why identifying divorced women over 45 is a key Big Data use case in Hadoop certifications. Learn how data analysis helps policymakers pinpoint economically vulnerable populations to design effective welfare and support programs.
Question
Why is the use case of identifying divorced women above 45 valuable for policy-making?
A. It identifies employment trends
B. It highlights vulnerable populations for welfare programs
C. It helps in taxation policy design
D. It measures female literacy levels
Answer
B. It highlights vulnerable populations for welfare programs
Explanation
Identifying divorced women above the age of 45 is a highly valuable use case in Big Data analysis for policy-making because this demographic represents a uniquely economically vulnerable population. Studies and demographic analyses consistently show that women entering their mid-to-late 40s and beyond following a divorce often face severe financial disruptions, including significant declines in household income, disrupted pension contributions, and a substantially higher risk of living in poverty compared to their married or widowed peers.
By using Hadoop and data analytics to isolate and quantify this specific demographic within census or socioeconomic data, governments and policymakers can accurately target and design specialized welfare programs, resource allocations, and safety nets (such as housing assistance, targeted healthcare, or pension adjustments) tailored to support them.
Options A, C, and D are incorrect because while this data could tangentially relate to employment or taxes, the primary, widely recognized socio-economic value of isolating this specific age and marital cohort is to address their documented financial vulnerability and need for social assistance.