You will get a cleaned, organized, and improved Excel or Google Sheets.
Project details
I help you turn messy spreadsheets into clean, organized, and ready-to-use datasets. Whether you need data standardized, duplicates removed, errors corrected, or formulas fixed, I provide fast, accurate, and reliable spreadsheet cleanup. Optional tiers include tailored calculations, column-specific transformations, or summary visuals to make your data actionable.
Data Tool
Google SheetsWhat's included
| Service Tiers |
Starter
$15
|
Standard
$40
|
Advanced
$80
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 4 days |
Number of Revisions | 1 | 2 | 2 |
About Noah
Data Analyst | Excel & Google Sheets Cleanup, Dashboards & Forecasting
San Francisco, United States - 10:37 pm local time
I specialize in:
📊 Designing interactive dashboards (Tableau, R Shiny) that empower teams to track KPIs and make data-driven decisions faster
🔄 Streamlining operations and optimizing processes to reduce waste and improve efficiency (I’ve cut project timelines by 25% in past roles)
📦 Building inventory and demand forecasting models that help businesses avoid stockouts and minimize excess inventory
With experience across VR/AR and energy sectors, I bring a strong analytical toolkit and a collaborative mindset to uncover hidden opportunities and align cross-functional teams.
Technical tools: Python (pandas, Matplotlib, NumPy, SciPy, seaborn), SQL, R (Tidyverse, ggplot, Shiny), Excel, MATLAB
Certifications: NASBA Certified in SQL Essentials and Production Analytics (CPE credits earned)
Whether you need dashboards, forecasting models, or custom analytics solutions, I’m here to help you make smarter, faster business decisions. Let’s connect and discuss your project!
Steps for completing your project
After purchasing the project, send requirements so Noah can start the project.
Delivery time starts when Noah receives requirements from you.
Noah works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review
I assess your dataset to understand its structure, issues, and your specific goals.
Data Cleaning
Remove duplicates, fix formatting inconsistencies, handle missing values, and correct errors.