Matrix Analysis is a branch of mathematics that focuses on the study of matrices, which are rectangular arrays of numbers or symbols. It involves various operations such as addition, multiplication, and finding determinants and inverses. This field is essential in solving systems of linear equations and is widely used in areas like statistics, computer science, and engineering. In Matrix Analysis, concepts like eigenvalues and eigenvectors play a crucial role. These concepts help in understanding the properties of linear transformations and are applied in fields such as machine learning and data science. Overall, matrix analysis provides powerful tools for analyzing and solving complex problems involving linear relationships.