Course Outline
Day 1
Core Principles of Data Products & Strategy
Introductory Overview of Modern Data Products
Distinguishing Data Products from Legacy Data Systems
Data as a Strategic Business Asset
Essential Elements of a Data Product Ecosystem
Pinpointing Business Challenges Amenable to Data Products
Summary of the Data Product Lifecycle (From Concept to Scale)
Case Studies: Precedents of Successful Data Products in Industry
Day 2
Data Product Design & Architecture
Foundational Principles of Data Product Design
Defining User Personas and Data Consumers
Data Architecture Models (Centralised vs Data Mesh vs Hybrid)
Engineering Scalable Data Pipelines
Data Modelling for Analytical and Operational Contexts
APIs and Data Accessibility Layers
Cloud Infrastructure for Data Products (Overview of AWS / Azure / GCP)
Day 3
Data Engineering & Implementation
Data Ingestion Techniques (Batch vs Streaming)
ETL vs ELT Frameworks
Constructing Robust Data Pipelines
Data Storage Solutions (Data Lakes, Warehouses, Lakehouse)
Data Transformation and Orchestration Toolsets
Foundations of Real-Time Data Processing
Practical Lab: Assembling a Basic Data Pipeline
Day 4
Analytics, AI Integration & Governance
Integrating Analytics into Data Products
Dashboards, KPIs, and Decision Intelligence
Introduction to AI/ML within Data Products
Recommendation Systems and Predictive Modelling
Data Quality Management and Monitoring
Data Governance, Privacy, and Compliance (GDPR overview)
Safeguarding Trust, Security & Reliability in Data Products
Day 5
Deployment, Scaling & Productisation
Productising Data Solutions for End Users
Deployment Strategies and CI/CD for Data Products
Monitoring, Performance Tuning & Scaling
Organisational Data Product Lifecycle Management
Monetisation Strategies for Data Products
Future Trends: Generative AI & Autonomous Data Products
Capstone Project Showcase & Feedback Session
Requirements
- A foundational grasp of data concepts and corporate reporting is advised.
- Proficiency in Excel or any fundamental data analysis tool is advantageous.
- An understanding of how data underpins business decision-making is beneficial.
- No advanced programming or technical expertise is necessary.
- A genuine interest in data, analytics, and digital product creation is mandatory.
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.