Aplicar técnicas de estatística multivariada e aprendizagem estatística para auxiliar a tomada de decisão em áreas específicas de organizações. Apply multivariate statistical techniques and statistical learning to assist decision making in specific areas of organizations.
Introdução; visual analytics; domínios específicos do business analytics: aplicações em áreas de marketing, recursos humanos, finanças, cadeia de suprimentos, detecção de fraudes. Introduction; visual analytics; specific business analytics domains: applications in the areas of marketing, human resources, finance, supply chain, fraud detection.
Introdução; histórico sobre business intelligence, business analytics e visual analytics; aplicações específicas com programação em Python e R: marketing analytics; RH analytics; financial analytics, supply chain analytics, detecção de fraudes. Introduction; background on business intelligence, business analytics, and visual analytics; specific applications with programming in Python and R: marketing analytics; HR analytics; financial analytics, supply chain analytics, fraud detection.
Bibliografia Principal Ramesh Sharda, Dursun Delen e Efraim Turban, Business Intelligence e Análise de Dados para Gestão do Negócio, Bookman, 2019, ISBN-13: 978-8582605196 Dinabandhu Bag, Business Analytics, Routledge 2016, ISBN: 978-1-138-91612-8. Christian Albright e Wayne L Winston, Business Analytics: Data analysis and decision making; Cengage Learning, 2012, ISBN: 978-1-305-94754-2. Benjamin Bengfort, Tony OjedaRebecca Bilbro, Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning, O’Reilly Media, 2018, ISBN: 978-1- 491-96304-3. Bibliografia Complementar Cole Nussbaumer Knaflic,Storytelling with data: a data visualization guide for business professionals, Willey, 2015, ISBN: 978-1-119-00225-3. Dean Abbott, Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst, Willey, 2014, ISBN: 978-1-118-72796-6.