AI Approaches
Business Perspectives and onboarding strategies
Business Perspectives and onboarding strategies
2 Day(s)
🎯 LEARNING OBJECTIVES
By the end of this lecture, you will be able to:
Understand the purpose and importance of Enterprise Architecture (EA) principles.
Explain how EA principles guide architecture decisions and technology investments.
Define effective principles across Business, Data, Application, and Technology Architecture.
Understand the relationship between business strategy, EA principles, and architectural decisions.
Apply EA principles to improve standardization, integration, reuse, security, scalability, and interoperability.
Establish measurable and enforceable architecture principles within an enterprise.
Understand how EA principles support governance, compliance, risk management, and digital transformation.
Identify common mistakes in defining and applying EA principles.
Apply EA principles to real-world architecture and transformation scenarios.
🧠 PREREQUISITES
Basic understanding of Enterprise Architecture concepts.
Familiarity with Business, Data, Application, and Technology Architecture.
Basic knowledge of business strategy and organizational objectives.
Basic understanding of software architecture and IT systems.
Familiarity with IT governance and architecture governance is beneficial but not mandatory.
Machine learning
Deep learning
Reinforcement learning
Prompt engineering
Front Office AI services
Agent-Based AI
Bots
Computer vision
Voice recognition
Generative AI
Conversational AI
Backoffice AI services
Predictive AI
Regression
Classification
Clustering
Anomaly detection
In-DB ML means running the machine learning directly inside the database, which is produced by modern database engines as follows:
SQL Server
sp_execute_external_script (Python/R), ML.NET integration
Oracle
OML
AutoML