Course
Outline
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 ill 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