Is this skill suitable for advanced Excel users?

Yes, while it covers basics, it excels at providing solutions for advanced scenarios like array formulas, nested logic, and sophisticated pivot table data modeling.

Can this skill assist with complex financial modeling?

Yes, it includes best practices for documenting assumptions, using named ranges, and structuring formulas for robust, error-free financial analysis.

Does it support Power Query and M code?

Absolutely. The skill includes specialized patterns for ETL processes and can generate M code to handle data transformation tasks more efficiently than standard formulas.

How does this skill help with Excel automation?

It provides Claude with the specific logic and M code syntax required to build repeatable Power Query transformations for automated data cleaning and preparation.

Excel Data Analysis

Name: Excel Data Analysis
Author: spjoshis

byspjoshis

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Data Science & ML

Empowers Claude to perform sophisticated data analysis, transformation, and reporting using advanced Microsoft Excel techniques and Power Query.

About

The Excel Analysis skill equips Claude with specialized expertise for handling complex business analytics and data management tasks within Microsoft Excel. It provides structured guidance for creating dynamic pivot tables, implementing advanced formulas like XLOOKUP and INDEX/MATCH, and automating ETL processes using Power Query and M code. This skill is essential for users needing to transform raw datasets into actionable insights, build robust financial models, or generate stakeholder-ready reports with professional formatting and data validation best practices.

Key Features

1 GitHub stars
Advanced Pivot Table configuration and calculated fields
Best practices for financial modeling and business calculation accuracy
Automated ETL workflows with Power Query and M code generation
Data cleaning, normalization, and structured table management
Complex formula implementation including INDEX/MATCH and array formulas

Use Cases

Building interactive dashboards and stakeholder-facing business summaries
Large-scale data cleaning and normalization for CRM and sales exports
Automated financial reporting and budget variance analysis

About

Key Features

1 GitHub stars
Advanced Pivot Table configuration and calculated fields
Best practices for financial modeling and business calculation accuracy
Automated ETL workflows with Power Query and M code generation
Data cleaning, normalization, and structured table management
Complex formula implementation including INDEX/MATCH and array formulas

Use Cases

Building interactive dashboards and stakeholder-facing business summaries
Large-scale data cleaning and normalization for CRM and sales exports
Automated financial reporting and budget variance analysis