Proficiency Level 1
Identifies the scope and features of data analysis tools.
Lists commonly used data analysis tools (e.g. WebFocus and Excel).
Documents the key uses and benefits of diverse data analysis tools.
Collects updated data analysis tools from industry publications.
Proficiency Level 2
Conducts a variety of data analysis projects, e.g. data mining and categorization.
Compares the uses and benefits of diverse data analysis tools.
Selects a data analysis tool for a specific case while minimizing risk (e.g. data loss).
Explains data analysis results from a business development perspective.
Monitors data processing procedures and adjusts data analysis tools accordingly.
Proficiency Level 3
Anticipates the need for data analysis tools based on the organization’s situation.
Evaluates diverse tools for data analysis and categorization functions.
Predicts risks in diverse data analysis tools and prepares contingency plans.
Appraises the associated costs and benefits of various data analysis tools.
Minimizes potential risks involved in the process of using data analysis tools.
Coaches others on the proper selection and use of various data analysis tools.
Proficiency Level 4
Subject Matter Expert
Designs new data analysis tools to increase data processing effectiveness.
Develops strategies to minimize potential risks when using data analysis tools.
Designs best practices to ensure the efficiency of data analysis, receipt, retrieval, etc.
Expounds on future developments in data analysis tools and their applications.
Establishes best practices in using data analysis tools to satisfy data analysis needs.
Develops a theoretical understanding of data analysis tools.