BUSI 358 - Data Science in Business

Data Science is a rapidly growing field focused on leveraging data to enhance business decisionmaking. With advancements in technology, businesses generate vast amounts of real-time, diverse data (Big Data), creating a high demand for professionals skilled in managing and analyzing this information. This course provides students with both theoretical foundations and practical applications of data science, emphasizing how data-driven insights can improve business performance. Students will explore methods to transform large volumes of business data into actionable insights, fostering value creation within the business ecosystem. Hands-on experience with popular analytical tools like Tableau, QlikView, and Datapine will enable students to analyze, visualize, and present data effectively.Upon completion of this course, students will gain an understanding of the foundations of data science and its applications. Understand how data science processes can be used to solve business problems. Understand concepts for extracting knowledge from data and value of data analytics. Understand and gain hands-on experience using analytics tools for data design, extraction, formatting, analysis, visualization and interpretation .Gain awareness of data ethics considerations

Data Science is an innovative field focused on uncovering and utilizing new methods for leveraging data to support business decision-making. With technological advancements enabling individuals and organizations to produce vast quantities of real-time, heterogeneous data (i.e., Big Data), there is a growing demand for experts capable of managing and analyzing this data effectively.This course provides students with both theoretical and practical foundations in data science. In today's knowledge economy, businesses achieve greater performance through data-driven, informed decision-making. Students will learn how large volumes of business-related data can be transformed into insights, allowing for a deeper exploration of the business ecosystem to create value.The course includes demonstrations of popular analytics tools, offering hands-on experience in analyzing, visualizing, and presenting data effectively. Tools such as Tableau Desktop, QlikView, and Datapine will be used to equip students with practical skills in data analytics.

None. But having taken these courses will be an added advantgae: MATH 204-Statistics for Social Science BUSI231-Introduction to Marketing and BUSI252-Introduction to Management Science

Dersle ilgili tüm bilgiler ve ders materyalleri dersin sitesinde bulunacaktır / Course related materials will be posted on the course web site.

·        Plagiarism will not be tolerated under any circumstances.·        No late submissions will be accepted, except in very rare cases (e.g., illness withmedical report, legal etc.).·        Students who are absent on an exam day must provide a legitimate excusebefore the exam. Failure to do so will result in a penalty of a grade of 0·        Any form of academic dishonesty (e.g., plagiarism, intellectual property theft – including materials taken from the Internet, having others do your assignments, failing to participate in group work, etc.) will result in a penalty.·        Students are expected to uphold the highest standards of academic integrity when using artificial intelligence (AI) tools. While AI resources may be used to support learning, all submitted work must reflect the student’s own understanding and effort.·        Unauthorized use of AI to generate or complete assignments, or failure to properly acknowledge such use when permitted, constitutes academic misconduct.