COURSES

Goals

The goal of the course is to provide basic knowledge of business intelligence and extend it with the knowledge and skills for strategic marketing decision-making. Firstly, the business and customer intelligence areas will be presented. Afterwards, we will focus on business and marketing strategies, their planning, development and practical application. Students should get acquainted with basic business tools like spreadsheets and databases. Multiple data sources, data quality and integration of data into data warehouses are the first major obstacle when implementing business intelligence solutions. We will focus on preparation and integration of data, how to resolve possible problems and typical pitfalls that we want to avoid. The main objective of the next part is to provide a deeper understanding of the nature and scope of marketing analysis and its role in strategic marketing. This includes investigating product-market opportunities, discovering unmet consumer needs, determining competitive advantage and forecasting customer behavior patterns so as to be proactive in the marketplace. Therefore, we will cover in detail problem-specific analytical methods and how they are applied in practice. The problems arising during this phase will also be indicated.

Curriculum

Scientific Method: Scientific knowledge structures, scientific activities/processes. Introduction: Definition of business intelligence (BI), definition of customer intelligence (CI), enterprise BI/CI architectures. Basic marketing approaches: Business informing, decision making, strategies, strategy planning and development, direct and indirect marketing strategies (product, offer, media, distribution and creative strategies), business models, analysis of marketing opportunities and environment. Basic business software tools: Data handling tools: Spreadsheets. Databases. Other tools. Examples, practical use at basic and advanced level. Data warehousing, data quality, data preparation/enhancement, data migration, data mediation. Predictive business analytics: Business problem definition, analysis, analytical modeling (descriptive/predictive modeling, metrics, customer centric profiling, customer scoring) for solving business/marketing problems, evaluation and business adoption of modeling results, overview of various industry examples such as credit scoring, risk scoring, churn prediction, customer retention, cross/upsell, fraud detection etc. Marketing automation: Customer/market analysis and research, contact strategies, marketing channels, integration aspects, creative tactics, content personalization, response tracking, marketing performance management, event- driven marketing, real-time marketing, best practice examples in various industries (banking, telecommunications, retail, insurance, and manufacturing), ethics and legal aspects. Challenges in software engineering and project implementation: A detailed overview of development of software project. Tools and Solutions: Overview of best-of-breed BI/CI tools and solutions in the marketplace. Use of AgI for BI.