Design and document analytical models and spreadsheets so they are auditable, maintainable, and easy for others to review and update. Core practices include structuring workbooks with a dedicated assumptions or inputs section, clearly separating raw data, detailed calculations, and summary outputs or key performance indicators, and applying consistent formatting, headers, and naming conventions. Avoid hard coded numbers by centralizing inputs, using named ranges and descriptive cell references, and documenting complex formulas with cell comments or explanatory notes. Maintain a documentation or readme sheet that explains model purpose, layout, assumptions, how to update inputs, and known limitations. Build validation checks and error flags, modularize logic for reuse, and design for scalability across larger data sets or additional time periods. Be prepared to explain sensitivities and scenario analysis, demonstrate how the model supports audit and review, and describe processes for versioning and change tracking.
EasyTechnical
0 practiced
You open a spreadsheet and discover hard-coded numeric values embedded inside formulas across multiple sheets. Outline a step-by-step remediation plan to centralize inputs, replace hard-coded numbers with references or named ranges, validate equivalence to original results, and document the changes for audit purposes.
HardTechnical
0 practiced
How would you design and implement unit tests for a financial spreadsheet model? Describe test case structure, examples of deterministic test inputs/expected outputs, automation options (Office Scripts, Python + openpyxl/pandas), how to store expected results (fixtures), and how to integrate tests into a CI/CD or scheduled validation pipeline for workbooks or Power BI datasets.
HardSystem Design
0 practiced
You are asked to convert a macro-heavy Excel workbook into a web-based reporting solution while preserving audit trails and user-level access. Outline migration options (Power BI with RLS and APIs for writeback, a web app with backend DB, or SharePoint with Power Automate), describe decision criteria (security, interactivity, writeback, audit needs), and propose a phased plan with validation gates and fallback options.
EasyTechnical
0 practiced
List 8–10 validation checks you would include in a monthly reporting model to detect common data issues (e.g., missing rows, mismatched totals, unexpected negative values). For each check, briefly say why it matters and how you'd implement it in Excel or Power BI (formulas, measures, or automated tests).
MediumSystem Design
0 practiced
Describe architecture and implementation options for adding automated validation checks that run during workbook open or dataset refresh, flag mismatches, and prevent report distribution until resolved. Cover approaches for Excel (VBA, Office Scripts), Power BI (measures, dataflows, pre/post refresh tests), and Looker (scheduled explores, data tests), including where to host check results and how to alert owners.
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