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 Duration 35 hours

Course Outline

Day 1

Foundations of Data Products & Strategy Introduction to contemporary data products Distinctions between data products and legacy systems Leveraging data as a strategic organizational asset Core components of a data product ecosystem Identifying operational challenges amenable to data product solutions Overview of the data product lifecycle (from conception to scale) Case Studies: Exemplary data products in the public and private sectors

Day 2

Data Product Design & Architecture Principles governing data product design Analysis of user personas and data stakeholders Evaluation of data architecture models (Centralized vs. Data Mesh vs. Hybrid) Designing scalable data pipelines for government use cases Data modeling for analytics and operational requirements APIs and data accessibility frameworks Cloud infrastructure for government data products (overview of AWS, Azure, and GCP)

Day 3

Data Engineering & Implementation Data ingestion methodologies (batch vs. streaming) Comparative analysis of ETL and ELT frameworks Constructing reliable data pipelines for public sector operations Data storage solutions (Data Lakes, Warehouses, Lakehouse) Data transformation and orchestration toolsets Introduction to real-time data processing Practical Exercise: Developing a foundational data pipeline

Day 4

Analytics, AI Integration & Governance Integrating analytics capabilities into data products Dashboards, KPIs, and decision support systems Introduction to AI/ML applications within data products for government services Recommendation systems and predictive modeling Data quality management and monitoring protocols Data governance, privacy, and compliance (overview of GDPR principles) Ensuring trust, security, and reliability in government data products

Day 5

Deployment, Scaling & Productization Productizing data solutions for internal and external stakeholders Deployment strategies and CI/CD pipelines for government data assets Monitoring, performance optimization, and scaling strategies Lifecycle management of data products within public agencies Monetization and resource optimization strategies for data products Future trends: Generative AI & autonomous data products Capstone Project Presentation & Feedback Session

Requirements

  • A foundational understanding of data concepts and business reporting is recommended.
  • Familiarity with Excel or basic data analysis tools is helpful.
  • An awareness of how data supports public sector decision-making will be beneficial.
  • No advanced programming or technical background is required.
  • An interest in data, analytics, and digital product development for government is essential.

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