Data Science and Blockchain

Curriculum

Module 1: How we got to now: the digital data transformation

• The origin of data-driven approaches in government, academia and business
• Progress in data factor markets
  • Data connectivity
  • Data storage
  • Data processing
• Quantification of everything
  • IoT
  • Smart Cities
  • Wearables
• A brave new world of perfect information

Module 2: Where data science is headed: the coming datapocalypse

• The dependency of data science on the theory of variance
• Why data centralization will kill traditional data science
• Why most organizations are ill prepared for the coming wave of data
• Why most organizations are totally unprepared for blockchain data

Module 3: Why blockchain is the solution for data science

• Blockchain as a data engineering solution
  • Defined quantification
  • Data completeness
  • Data trustworthiness
• Blockchain as a data analytics solution
  • Data access and preparation
  • Data scope and data totality improvements
  • New data science frameworks

Module 4: Examples of successful blockchain data science projects

• Use cases by vertical
  • Finance
  • Ecommerce
  • Healthcare
  • Fintech & SaaS
• Use cases by organizational type
  • SMBs
  • Enterprises
  • Government
  • NGOs
• Use cases by organizational department
  • Business Intelligence
  • Marketing
  • Customer Experience Management
  • Procurement & Fulfillment

Module 5: How to get started with your first blockchain-based data science project

• Offensive strategies for adopting blockchain into data science workflows
  • Data maturity stage audit
  • Prioritizing blockchain data science projects
  • Build or buy blockchain data science solutions
• Defensive strategies for adopting blockchain into data science workflows
  • Competitive intelligence and secondary research
  • Macro metric correlations for blockchain data science models
  • Game theory and “best response” actions