Data Science Impact on Social Welfare Program Administration
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The adoption of data science within social welfare organizations is not complete or fully developed. The administration of social welfare programs with data science provides an opportunity for more efficient and targeted social welfare assistance. The collection of data on social programs, the advancement of data science, and the current applications within social welfare systems lay the groundwork from which a successful integration could be done. This paper discusses the tenants of these three areas and what they lend to the adoption of data science in social welfare programs. The benefit to social welfare programs that choose to embrace data science in their organizations will be immense. The lack of current data science integration into social welfare systems is not intentional or an insurmountable obstacle. The current barriers to the integration of data science into social welfare systems consist of a lack of knowledge, data policy governance, and data integration (Vought, 2019). The current advancements in these areas show a desire for a more open and integrated data science approach to administering and advancing social welfare. This paper addresses each of these specific areas and the advancements which have taken place. These advances enable the future integration of data science into social welfare programs.