A.[1] Business and [2] IT

B.[1] Governance and [2] Management

C.[1] Strategy and [2] Execution

D.[1] Technology and [2] Data

A.The Enterprise data architecture, data security practices and industry regulations

B.Data Stewardship Metrics, Data Governance, Business Drivers

C.Vision/Mission statement, Data quality framework, Data stewardship metrics

D.Vision/Mission Statement, Data Governance data principles, Business drivers

E.Data processes, data principles and the timeframe for implementation

A.Regression

B.Confidence level

C.Regulation

D.Confidentiality level

A.Working with external stakeholders to assess data quality

B.Using more data sets with diverse data sources

C.Remove sources of likely bias from data sets before analysis

D.Using more data sets with same data

E.Re-baselining the data set after each period of analysis to remove assumptions

A.Unsupervised learning

B.Reinforcement learning

C.Artificial learning

D.Supervised learning