Collecting, cleaning, and analyzing data into insights that drive decisions, using statistics and visuals.
Data analysis is discovering patterns in raw data to support business decisions. It spans collection, cleaning, exploratory analysis, statistical testing, visualization, and communication. The core is asking the right questions, finding answers through data, and connecting them to action.
SFIA 9 defines data analytics competency across 7 levels from Level 2 (assist) to Level 6 (lead), providing autonomy and complexity criteria directly used for level boundary setting.
Entry-Level, Mid-Level, Senior 3-tier structure with Analytical/Technical tracks, reflecting stage-specific competency differences in checklist behavior criteria.
Awareness-Comprehension-Application-Influence 4-stage proficiency framework providing governmental authority as an accredited data competency standard.
Presents a 5-stage analytics maturity model (Analytically Impaired to Analytical Competitors) with organizational analytics culture case studies, providing practical grounding for L4-L7 checklists on quantifying business impact and establishing organizational analytics systems.
