Tools, Frameworks & Implementation Proficiency Topics
Practical proficiency with industry-standard tools and frameworks including project management (Jira, Azure DevOps), productivity tools (Excel, spreadsheet analysis), development tools and environments, and framework setup. Focuses on hands-on tool expertise, configuration, best practices, and optimization rather than conceptual knowledge. Complements technical categories by addressing implementation tooling.
Aggregation Functions and Group By
Fundamentals of aggregation in Structured Query Language covering aggregate functions such as COUNT, SUM, AVG, MIN, and MAX and how to use them to calculate totals, averages, minima, maxima, and row counts. Includes mastery of the GROUP BY clause to group rows by one or more dimensions such as customer, product, region, or time period, and producing metrics like total revenue by month, average order value by product, or count of transactions by date. Covers the HAVING clause for filtering aggregated groups and explains how it differs from WHERE, which filters rows before aggregation. Also addresses related topics commonly tested in interviews and practical problems: grouping by multiple columns, grouping on expressions and date truncation, using DISTINCT inside aggregates, handling NULL values, ordering and limiting grouped results, using aggregates in subqueries or derived tables, and basic performance considerations when aggregating large datasets. Practice examples include calculating monthly revenue, finding customers with more than a threshold number of orders, and identifying top products by sales.
General Technical Tool Proficiency
Familiarity and practical experience with technical productivity and analysis tools such as SQL, Python or R, data visualization platforms like Tableau and Power BI, Excel, and statistical or analytical software. Candidates should be able to describe depth of expertise, typical use cases, examples of real world applications, automation or scripting practices, and how they select tools for different problems. This topic includes discussing reproducible workflows, data preparation and cleaning, visualization best practices, and integration of tools into cross functional projects.
Business Intelligence Tools and Features
Covers expert proficiency with major business intelligence tools such as Tableau, Power BI, and Looker, and the advanced capabilities these platforms provide. Topics include creating calculated fields and parameters, conditional formatting, complex filtering, dashboard interactivity and responsive layout design, and best practices for visualization and user experience. Includes performance optimization techniques such as extract versus live connection trade offs, query optimization, incremental refresh strategies, and general performance tuning. Also covers governance and security features including access controls and sharing models, considerations for tool selection and recommending the right tool for a specific use case, and high level migration strategies between BI platforms.
Excel Proficiency for Finance
Advanced Excel skills specific to finance: building financial models, creating dashboards, using formulas for calculations, pivot tables, data visualization, scenario analysis, sensitivity analysis. Be comfortable with absolute vs. relative references, named ranges, and financial functions like NPV, IRR.
Analytical Modeling and Documentation
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.
Excel Modeling and Analysis
Focused evaluation of advanced spreadsheet skills and model design using Excel. This covers building robust formulas and complex functions, data analysis tools such as pivot tables and aggregation functions, filtering and lookup techniques, creating dynamic models with scenario tables and sensitivity analyses, and producing clear data visualizations. It emphasizes model organization and best practices including separating inputs and assumptions from calculations and outputs, consistent cell referencing, documenting assumptions and logic, error checking and validation, avoiding unintended circular references, and designing flexibility for changes to assumptions. Interviewers may ask for examples of models built, walk through of design decisions, and discussion of testing and maintenance approaches.
Excel Core Functions and Formula Mastery
Strong proficiency with essential Excel functions: VLOOKUP and INDEX-MATCH for data lookups, IF and nested IF statements for logic, SUM/SUMIF/SUMIFS for conditional aggregation, PivotTables for data summarization, TEXT functions for formatting, IFERROR for error handling, COUNTIF/COUNTA for counting. Build efficient, understandable formulas that other people can audit and modify. Understand formula best practices and when to use each function type.
Data Analysis, Summarization, and Visualization
Proficiency in sorting, filtering, and manipulating financial data; creating PivotTables to summarize data by multiple dimensions; building charts and graphs that effectively communicate financial insights; using conditional formatting to highlight key metrics, exceptions, or trends; creating dashboard-style summaries. Focus on clarity and business storytelling—visuals should communicate insights, not just display data.
Date and Time Operations
Tests practical skills for working with dates and times in analysis and operations. Candidates should be comfortable with date filtering, date comparisons, relative date ranges such as last n days or rolling windows, fiscal period calculations, and basic date functions used in queries and reporting. Interviewers assess ability to translate business reporting needs into correct date logic, handle edge cases such as time zones and inclusive versus exclusive ranges, and apply these skills in contexts like sales pipeline aging, period over period comparisons, and performance windows.