Appendix 3: Data Literacy Competencies
THE FOLLOWING ARE THE 10 data literacy competencies discussed in the BP 2 section of Chapter 8.
Data architecture Data architecture is the models, policies, rules, and standards that govern which data is managed in the data lifecycle in organizations.
Data acquisition Data acquisition is the process of digitizing data from the world around us so it can be stored and processed in an IT system.
Master data management Master data management (MDM) is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise's official shared master data assets. Master data is the consistent and uniform set of identifiers and extended attributes that describe the core entities of the enterprise including customers, prospects, citizens, suppliers, sites, hierarchies, and chart of accounts.
Data engineering This is the practice of designing and building systems for collecting, storing, and analyzing business data and metadata at scale. It also includes the knowledge and skills to determine if data are clean and if they use the best method and tools to take necessary actions to resolve any problems to ensure data is in a suitable form for analysis.
Data ethics The knowledge that allows a person to acquire, use, interpret, and share data in an ethical manner including recognizing legal and ethical issues (e.g., biases, privacy).
Statistical modeling ...
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