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 and tutorials for post-processing lecture sessions. The corresponding content is available in the folder demo_notebooks. We use the Python programming language and share content as Juypter notebooks.
The repository also provides exercises for you to work on (see folder excercises). You are supposed to solve these exercises on your own. We will offer a Q&A session to discuss any questions you came accross when working on the exercise tasks and provide help. However, solutions to exercise notebooks will typically not be shared.