You will get accurate Data Entry, Cleaning, and Final Report with Pivot Tables
Project details
Need clean, reliable data fast? I offer meticulous data collection, entry, and cleaning services to deliver spreadsheets ready for immediate reporting. As a beginner committed to earning a 5-star reputation, my primary focus is 100% accuracy and structured data formatting. I use Excel and Google Sheets to transform your raw sources (URLs, documents) into a perfectly organized, useful dataset.
Data Tool
Microsoft ExcelWhat's included
| Service Tiers |
Starter
$10
|
Standard
$15
|
Advanced
$20
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 6 days |
Number of Revisions | 1 | 2 | 3 |
Number of Pages Mined/Scraped | 5 | 10 | 15 |
Number of Sources Mined/Scraped | 1 | 2 | 3 |
Optional add-ons
You can add these on the next page.
Additional Revision
+$2
Source Verification
+$5About Dilnoza
Big Data Engineer | Analyst | Azure & AWS | ETL & DWH Architect
Tashkent, Uzbekistan - 10:04 pm local time
My path into data engineering is a bit unusual. Before transitioning into tech, I earned a Master's in TESOL and spent years as an English educator. Why does this matter for your project? Because my biggest strength isn't just writing Python or SQL; it's communication. When you work with me, you won't deal with language barriers, poorly written documentation, or confusing tech jargon. I know how to explain complex data architecture in clear, simple English.
I am currently finishing my MSc in Business Intelligence & Analytics, and I specialize in the heavy lifting of data engineering. I don't just build dashboards; I build the engines that make those dashboards possible.
Here is what I actually do:
• Big Data Processing: I recently built a pipeline to clean and process a 100GB dataset containing over 2 billion records using Apache Spark (PySpark) and Azure Synapse.
• Data Warehousing & ETL: I design Star and Galaxy schemas from scratch. I regularly write Python and SQL scripts to extract messy data from APIs, XML, JSON, and CSVs, clean it, and load it into reliable databases.
• Backend & Analytics: I use Go (Golang) for fast backend services, and I understand the business side of data (forecasting, Tableau) so I know exactly how your data needs to be modeled for the end user.
My Core Stack:
• Python (Pandas, NumPy) & Go (Golang)
• SQL (MS SQL Server, PostgreSQL)
• Azure (Synapse, Data Lake) & PySpark
• Hadoop, Hive, ETL/ELT pipelines
Whether you are dealing with a broken data pipeline, need to migrate messy data into a clean warehouse, or have a dataset that is just too big for your current setup, I’d love to help.
Send me a message, and let's hop on a quick call to chat about your data.
Steps for completing your project
After purchasing the project, send requirements so Dilnoza can start the project.
Delivery time starts when Dilnoza receives requirements from you.
Dilnoza works on your project following the steps below.
Revisions may occur after the delivery date.
Data Collection & Initial Entry/Cleaning
I carefully gather data from the provided sources (URLs, PDFs, documents) and input it into the designated format (Excel/Sheets). I run cleaning processes (removing duplicates, correcting formatting errors, standardizing entries).
Reporting and Summarization
Data is organized into pivot tables or a summary report for quick business insights.