Day 1: Establishing the Data and Decision Foundation

Value of Analytics and Business Intelligence

• Convert technology potential into outcomes
• Distinguish activity from realized value
• Identify assumptions affecting benefit realization
• Build value case for decisions

Analytics Data Quality

• Identify data required for analysis
• Review completeness consistency and timeliness
• Resolve quality issues before use
• Draft data-quality checklist for dataset

Analytics Decision Questions

• Convert business concerns into questions
• Link each question to decision
• Define evidence needed for answers
• Remove questions lacking actionable value

Day 2: Preparing Data and Building Analytical Models

Analytics Data Preparation

• Define minimum data needs clearly
• Compare reliability across data sources
• Standardize data fields for analysis
• Prepare concise data-quality summary

Analytics Descriptive and Diagnostic Models

• Summarize outcomes using reliable measures
• Segment results into meaningful groups
• Investigate drivers behind significant variation
• Distinguish correlation from proven causation

Predictive Analytics and Scenario Estimation

• Define outcome requiring estimation
• Select drivers with explanatory value
• Compare scenarios instead of forecasts
• Communicate uncertainty alongside predicted results

Day 3: Designing Indicators, Dashboards, and Data Stories

Analytics KPI Selection

• Identify KPIs linked to decisions
• Link KPIs to expected value
• Verify data availability for KPIs
• Build concise KPI shortlist

Designing Information Dashboards

• Define decisions supported by dashboard
• Select measures aligned with decisions
• Organize visuals around priority questions
• Remove displays lacking decision value

Visual Storytelling of Results

• Lead with evidence-supported message
• Choose visuals suited to comparison
• Annotate important shifts without clutter
• Connect findings to recommended action

Day 4: Governing Data, Access, and Decision Quality

Analytics Data Governance

• Define decision execution assurance roles
• Link controls to technology risks
• Capture compliance evidence consistently
• Assess governance maturity improvement priorities

Analytics Privacy and Access

• Classify sensitive information before use
• Limit access to legitimate needs
• Apply approved sharing storage controls
• Escalate uncertain privacy cases

Quality of Evidence-Based Decisions

• Link analysis to business priorities
• Test assumptions using relevant data
• Compare patterns across meaningful segments
• State conclusions with appropriate limitations

Day 5: Embedding Analytics in Management Decisions

Embedding Analytics into Workflows

• Frame analysis around management decision
• Select evidence answering decision questions
• Verify results before recommending action
• Present findings in business language

Assessing Value and Improving Models

• Select measures for intended outcomes
• Establish baselines and target levels
• Explain variation before final conclusions
• Use indicators to trigger intervention

Applied Analytics Project

• Align project with business priorities
• Check assumptions using relevant data
• Contrast patterns across key segments
• State conclusions with suitable limitations

• Practical examples examining value of analytics and business intelligence and its workplace implications
• Group exercises building working tools for predictive analytics and scenario estimation
• Scenario testing of privacy, security, and access control with feedback and revision
• An integrated application producing an analysis brief covering applied analytics project