Date of Award


Document Type


Degree Name

Master of Science in Information Systems and Technology


Information and Decision Sciences

First Reader/Committee Chair

Benjamin Becerra


Immigration is one of the most hotly debated topics in the US. Merely taking a look at the types of immigrant and non-immigrant visas issued by the US government, one can realize the complexity of the law governing the numerous intricacies involved with the issue of immigration (Golash-Boza, 2009). With the ever-increasing population of immigrants in the US, a good understanding of immigration’s impact on the US society is more important than ever before. The objective of this project was to increase our understanding of immigration’s impact on the US society by investigating the general trends in Visa Applications, employers, cities, economic factors and highlighting the important observations. The important findings are: (a) The number of applications have increased, while the number of denials seem to taper off. (b) The most non-immigrant visa applications are filed by employers in a few major cities, most of them being IT companies. (c) Advanced manufacturing is one of the major sectors requiring the workforce from other countries besides IT, which takes up more than 45% of the application share. (d) H-1B visas are a clear outlier among the total non-immigrant visa applications. (e) Similarly, California is an outlier state among all the US Perm applications. (f) The immigrant workforce earns less than the natives when they enter the country. However, their salary grew gradually, and they actually end up earning significantly higher. (g) The recent immigrants tend to be more educated when compared to US-born and total immigrants. The conclusion of the study is that immigration overall is beneficial to the American society from economic as well as cultural aspects and makes America an attractive destination for talented, highly skilled individuals. Future work should focus on keeping this analysis up to date with the latest data and potentially making this analysis available in the form of a website. Machine learning can also be used to find patterns that are not easily recognized by means of this study.