Data analytics represents an institutional discipline focused on transforming raw data into structured insights that support organizational decision systems. Its relevance lies in enabling evidence based analysis, performance visibility, and strategic alignment across functions. This training program presents analytical concepts, data structures, and interpretation models used within modern organizational environments. It provides a structured perspective on how data supports planning, evaluation, and informed decision making.
Identify core data analytics concepts and analytical domains.
Analyze data structures and sources used in organizational contexts.
Evaluate analytical models supporting descriptive and diagnostic insight.
Assess the role of data analytics in performance measurement and reporting.
Examine governance considerations influencing analytics reliability and use.
Managers and decision-makers.
Business and performance analysts.
Strategy and planning professionals.
IT and data coordination staff.
Professionals involved in reporting and evaluation.
Definition and scope of data analytics within organizations.
Types of data and data source classification structures.
Descriptive, diagnostic, predictive, and prescriptive analytics overview.
Data quality dimensions and reliability considerations.
Institutional role of analytics in decision support.
Data aggregation and transformation logic.
Analytical frameworks for trend and pattern identification.
Visualization structures supporting insight communication.
Interpretation models linking data outputs to business context.
Limitations and bias considerations in analytical interpretation.
Data governance and ownership frameworks.
Ethical and compliance considerations in data analytics use.
Performance measurement systems supported by analytics.
Integration of analytics into strategic and operational reporting.
Organizational maturity models in data driven decision systems.