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
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 will be prepared for the coming wave of data
- Why most organizations are totally unprepared for blockchain data
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
4. Examples of successful blockchain data science projects
- 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
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