Course Outline
Day 1
Fundamentals of Data Solutions & Strategy
Introduction to Contemporary Data Solutions
Data Solutions Compared to Traditional Information Systems
Information as a Strategic Business Asset
Core Elements of a Data Solution Ecosystem
Identifying Commercial Challenges Suitable for Data Solutions
Overview of the Data Solution Lifecycle (Ideation to Scaling)
Case Studies: Successful Data Solutions in Industry
Day 2
Architecture & Design of Data Solutions
Principles of Data Solution Design
Understanding User Personas and Information Consumers
Data Architecture Models (Centralized vs Data Mesh vs Hybrid)
Designing Scalable Data Pipelines
Data Modeling for Analytics and Operational Use
APIs and Data Accessibility Layers
Cloud Infrastructure for Data Solutions (AWS / Azure / GCP overview)
Day 3
Data Engineering & Execution
Ingestion Methods (Batch vs Streaming)
ETL vs ELT Frameworks
Constructing Reliable Data Pipelines
Storage Solutions (Data Lakes, Warehouses, Lakehouse)
Transformation and Orchestration Tools
Introduction to Real-Time Processing
Practical Lab: Constructing a Simple Data Pipeline
Day 4
Analytics, AI Integration & Governance
Integrating Analytics into Data Solutions
Dashboards, KPIs, and Decision Intelligence
Introduction to AI/ML in Data Solutions
Recommendation Systems and Predictive Models
Quality Management and Monitoring
Governance, Privacy, and Compliance (GDPR concepts overview)
Ensuring Trust, Security & Reliability in Data Solutions
Day 5
Deployment, Scaling & Productization
Delivering Solutions to End-Users
Deployment Strategies and CI/CD for Data Solutions
Monitoring, Performance Optimization & Scaling
Lifecycle Management of Data Solutions in Organizations
Monetization Approaches for Data Solutions
Future Trends: Generative AI & Autonomous Data Solutions
Capstone Project Presentation & Feedback Session
Requirements
- A foundational grasp of data concepts and business reporting is advisable.
- Experience with Excel or similar basic analytical tools is advantageous.
- Insight into how information supports corporate decision-making is beneficial.
- No sophisticated programming or technical background is necessary.
- An enthusiasm for data, analytics, and digital solution development is essential.
Testimonials (2)
The variety of the information shared and the clarity to explain terms in plain English.
Arisbe Mendoza - Fairtrade International
Course - GDPR Workshop
It's a hands-on session.