From "Information Technology Competency Model: September 2012"
Employment and Training Administration, United States Department of Labor
2. Databases and Applications: The use of technology to control and safeguard the collection, organization, structure, processing and delivery of data.
Critical Work Functions:
* Understand fundamental concepts of database design and the need for database architectural strategies to fit business or industry requirements
* Differentiate between databases and flat files
* Differentiate between hierarchal and relational databases
* Understand metrics used to characterize data and different kinds of data (structures, unstructured, text-based, character limits)
* Understand importance of very large, unstructured data sets that have to be managed and queried in new ways to find meaning and value (“Big Data”)
* Demonstrate ability to analyze data requirements
* Demonstrate familiarity with common database administration and maintenance tasks
* Follow information management standards and guidelines
* Understand purpose and process of coding and tagging information
* Demonstrate ability to find and select the information, appropriate tools, and processing techniques needed for a task
* Understand logical and physical components of an information storage infrastructure
* Explain the role and relationships of data, information, and databases in organizations, specifically their role in in business intelligence
* Describe mechanisms for data collection and management, e.g., automated data collection, input forms, source documents, external devices, interfaces, relational characteristics, and dependencies
* Assess the quality, accuracy, and timeliness of given data
* Demonstrate knowledge of managing data as official records
* Demonstrate knowledge of identifying and protecting privacy data and sensitive information
* Be able to create and query a basic database
* Understand how other applications interact with databases to create and retrieve data

Technical Content Areas:
Data Administration
* Concepts and fundamentals of data management
* Data integration
* Data modeling
Database Management
* Data architecture
* Data storage (online, near-line, archive)
* Database query languages
* Managing the database environment
* Metadata
* Semantic Web
* Special-purpose databases
* Use of graphical vs. textual representations of database structures
Data models
* Dimensional models
* Flat files
* Hierarchical model
* Logical databases
* Network model
* Object databases
* Object-relational databases
* Relational model
* Semantic models
Business Intelligence
* Competitive intelligence
* Data analytics
* Data mining
* Data warehousing
* Predictive data modeling
* Web analytics
Data Protection
* Archiving
* Data encryption
* Data masking