Welcome to the business analytics and data science – BADS – repository ...
BADS is a master-level lecture offered by members of the Chair of Information Systems of the Humboldt-University of Berlin.
Data is omnipresent. Often called "the new oil" to emphasize its value for economy, the data gathered by a business organization is an asset that, if properly cultivated, facilitates improving operations, decision-making, and, by extension, gaining competitive advantage. Data sciece is an interdisciplinary field concerned with turning data into insight, actions, and ultimately utility. The boundaries between business analytics and data science are not clear cut. We understand data science as a concept emphasizing methodologial aspects and business analytics as a concept emphasizing applications of the corresponding methodologies in business. BADS strives to achieve a healthy balance between both, methods and applications. More specifically, we aim at equiping students with a solid understanding of empirical models for data-driven decision support, the technical expertise to design, estimate, tune, use, and diagnose the corressponding models to judge their adaquacy, and the ability to communicate data- and model-based insights to stakeholders in business organizations.
The repository provides demo codes for the tutorial session, which revisit the lecture. The corresponding content is available in the folder tutorial_notebooks. We use the Python programming language and share content as Juypter notebooks.
The repository also provides exercises for you to practice your coding skills (see folder excercises). The exercises are provided for self-study. We will not discuss the task or their solutions in the course. However, we offer a Q&A session to discuss any questions you came accross when working on the exercise tasks and provide help.