You will get Clean, Organized, and Formatted Data for Accurate Analysis
Project details
I clean data with the end-goal in mind. Because I understand web-based visualization, I organize your data so it’s ready to plug directly into your dashboards for immediate storytelling.
Data Tool
Microsoft ExcelWhat's included
| Service Tiers |
Starter
$15
|
Standard
$50
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 2 | 5 |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $40
Additional Rows
(+ 1 Day)
+$10Frequently asked questions
About Morne
Data Analyst
Roodepoort, South Africa - 6:00 pm local time
My mission is simple: I clean and refine your data so you can stop wrestling with spreadsheets and start uncovering real insights. I believe that the best decisions are built on a foundation of quality. Having spent two decades in finance, I prioritize the accuracy and safety of your sensitive information above all else. You can trust that your data is in secure hands.
I bridge the gap between complex data and business strategy using a robust technical toolkit, consisting of SAS, Python and Excel/Google Sheets.
I am a lifelong tech enthusiast who loves a challenge and is always eager to learn new ways to solve old problems.
Let’s get your data to tell the story it was meant to tell! I look forward to helping you find the clarity your business deserves.
Steps for completing your project
After purchasing the project, send requirements so Morne can start the project.
Delivery time starts when Morne receives requirements from you.
Morne works on your project following the steps below.
Revisions may occur after the delivery date.
Secure Data Sourcing & Integration
I begin by securely ingesting your raw data from its source (Excel, Google Sheets or CSV). I ensure the transfer is handled with the highest security protocols, maintaining integrity and confidentiality of your data from the very first minute.
Quality Evaluation & Diagnostic
I perform a thorough audit of the dataset. I identify "dirty" data points, missing values, structural inconsistencies and outliers. This diagnostic phase allows me to map out exactly what needs to be fixed to ensure the final output is 100% reliable.