Start with the business responsibility, desired outcome and current way of working.
AI for Spreadsheet Analysis
Use AI to clean business data, develop formulas, explore trends, investigate exceptions and prepare clearer findings.
Practical applications
What this training can help your people do.
Delegates work through relevant examples using the organisation’s approved or best-fit AI platform. They learn transferable methods—not dependence on a particular provider.
- ✓Understand the business question, dataset structure, field meanings and expected decisions
- ✓Clean, classify and restructure messy data while preserving an auditable source copy
- ✓Create, explain, troubleshoot and improve formulas, lookups, tables and calculations
- ✓Analyse trends, variances, exceptions, correlations and possible operational drivers
- ✓Build PivotTables, charts, dashboards and concise management summaries where appropriate
- ✓Use Universal Prompts and a reusable Project or work environment to retain analysis instructions
- ✓Develop a repeatable analysis workflow or basic assistant for recurring imports, checks, reporting and commentary
- ✓Test formulas, reconcile totals, challenge assumptions and verify every important conclusion against source data
The Streamline Intel Method
From a useful example to repeatable business capability.
Training combines ordinary-language instruction, Streamline Intel Universal Prompts, guided exercises, reusable Projects, configured AI work environments, basic AI assistants or agents, and repeatable workflow methods. Delegates learn how to provide context, use approved information, define the required output, review the result and improve the method for future use. Configuration and available features depend on the approved platform, programme scope, subscriptions and permissions.
Use clear prompts, relevant files and guided practical exercises.
Check facts, figures, permissions, assumptions and professional quality.
Turn successful work into an adaptable prompt, Project or repeatable workflow.
No coding or previous AI expertise is required. Important outputs remain subject to human review, organisational policy, privacy requirements and professional approval.