Data Science uses mathematics, computer science, and machine learning to identify patterns in large data sets and has been rapidly expanding because of its huge potential and the availability of data. It has the ability to discover new sources of data and use them to create meaningful information. It involves understanding the underlying trends, patterns, and insights for a given dataset. Data Science incorporates analytical thinking and processes such as data preparation, analysis, and communication of insights. The use of Data Science has grown rapidly in recent years, with the emergence of tools such as Hadoop, Spark, and other distributed databases that can handle large datasets. Companies use Data Science for competitive advantage as it enables them to gain insights into customer needs, preferences, and trends. Companies also use Data Science to gain a better understanding of their businesses by analyzing their data to uncover new opportunities. Data science is the practice of leveraging advanced methods in mathematics, modeling, and statistical analysis to gain the understanding of large amounts of data. It involves using various techniques including linear algebra, machine learning, numerical optimization, natural language processing, text analysis, visualization, and data mining to extract insights from data. The goal of data science is to improve the decision-making process of a company or organization by providing insights that guide decision makers through the decision process. This is done by locating, obtaining, and analyzing data. After analyzing the data, insights are generated that help companies or organizations to gain a thorough understanding of their customers, products, and operations. They use data to construct models that can be used to investigate different phenomena, such as marketing trends or customer spending patterns.