This case study showcases an end-to-end Excel workflow where raw, unstructured electricity consumption data was cleaned, structured, and transformed into an interactive, decision-ready report.

The focus was on converting messy data into a format that founders and small teams can easily analyze, filter, and explore—using Excel alone.

The dataset was delivered in a highly unstructured format, with date, time, and electricity usage values combined into a single column.

With over 8,700 rows, the data could not be:

Filtered

Analyzed

Or visualized effectively in its original form

Cleaned and structured 8,700+ rows of raw data

Extracted date, time, and KWH into separate, usable columns

Standardized formats for consistency and accuracy

Prepared the dataset for analysis using Excel formulas and AI-assisted features

Built pivot tables to analyze electricity usage by month, day, and time

Added slicers for quick, interactive filtering

Applied conditional formatting to highlight usage patterns

Designed a clean, readable dashboard for fast insights

Completed the full workflow in ~20 minutes end-to-end

Cleaned and structured 8,700+ rows of data

Delivered a fully interactive Excel dashboard

Converted raw data into a client-ready reporting solution that supports faster, clearer decisions