Senior Management Programme In Business Analytics

Program Curriculum

• The business value of data analytics

  • Analytics readiness of an organisation and building a data-driven decision making culture
  • Building organisational capability for making use of analytics
  • Appreciating the emerging nature of competition and the role of business analytics

• Statistics for analytics

  • The art of summarising data and statistical learning in decision- making
  • Applied probability and decision-making under uncertainty
  • Regression techniques and the art of capturing relationships among variables of interest
  • Data sampling and the art of inferring about the population from samples

• Data sources

  • RDBMS, unstructured data and other forms of data
  • Data extraction and cleaning
  • Dimensionality and outlier analysis

• Descriptive analytics

  • Appreciation of analytical reasoning and empirical findings from data
  • Challenges in data visualisation and data interpretation
  • Interpretation of raw data
  • Interpretation of statistical summary of data

• Experimentation

  • Identifying a business problem
  • Creating a hypothesis to solve the business problem
  • Defining parameters that validate the hypothesis
  • Testing the hypothesis through analysis
  • Interpreting the results of the analysis

• Predictive analytics

  • Business forecasting principles and issues
  • Artificial Intelligence and Machine Learning in decision-making – the role of supervised learning
  • Role of supervised and unsupervised learning in decision-making
  • Time series analysis based decision-making
  • Combining human expertise with data-driven intelligence for decision-making
  • Artificial neural network and deep learning in decision-making

• Prescriptive analytics

  • Learning through simulation and games
  • Individual and group decision making issues
  • Use of discrete optimisation concepts in decision-making
  • Insights from game-theoretic situations, network externalities and network effect on the economy,
  • Information cascade effects in decision-making

• Global perspectives of business analytics

  • Business analytics case studies from Europe, North America, China, Japan, Asia
  • GDPR and emerging data privacy laws and concerns across the globe
  • Data security concerns and best practices across the globe