Data Science and Analytics is an interdisciplinary field that originates from statistics, mathematics, and computer science. Its foundations were laid in the early 20th century with the introduction of statistical methods into scientific research. The development of computers in the 1940s and 1950s enabled faster data processing and brought a new dimension to data analysis. The emergence of database systems in the 1960s and 1970s, followed by decision support systems and artificial intelligence studies in the 1980s, helped make data-related analyses more systematic.

 With the emergence of the concept of “data mining” in the 1990s, the process of extracting meaningful information from large datasets began to be addressed as a scientific field. After the 2000s, the widespread use of the internet, social media, mobile technologies, and digital systems led to the rise of big data, transforming data science and analytics into an independent discipline. During this period, data science evolved as a field that combines statistical analysis with machine learning and artificial intelligence methods, encompassing the stages of data collection, cleaning, analysis, modeling, and interpretation of results.

 In Türkiye, studies in the field of data science and analytics gained momentum particularly after the 2000s. Initially, the field developed through courses and academic research within statistics, computer engineering, and industrial engineering departments. From the 2010s onward, with the increasing adoption of digitalization, Industry 4.0, and artificial intelligence applications, universities began to offer undergraduate and graduate programs focused on data science, data analytics, and big data. Today, many public and private universities in Türkiye offer Data Science and Analytics departments or programs related to this field.

 Professionals working in the field of data science and analytics contribute to organizations’ ability to make accurate and timely decisions by transforming data into meaningful insights. Data scientists and data analysts analyze data, build models, make predictions, and present these results in a clear and understandable way for decision-makers. The main objectives are to improve processes, reduce risks, identify opportunities, and provide strategic insights for the future.

 Graduates of this field have employment opportunities across a wide range of sectors, including information technology, finance, healthcare, manufacturing, energy, e-commerce, marketing, telecommunications, consulting, public institutions, and academia. They can work in positions such as data analyst, data scientist, business intelligence specialist, machine learning engineer, and decision support systems expert. As data has become a strategic asset, data science and analytics has emerged as a profession at the core of digital transformation, with its importance steadily increasing. In this context, data science and analytics has become an indispensable discipline for enhancing organizational competitiveness, ensuring sustainable growth, and supporting effective decision-making.