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Fiverr Pro
English
$
USD
I will do data analysis, data cleaning, and interactive power bi dashboards
About this Gig
Looking for a professional Data Analyst to clean your data, write powerful queries, or build an interactive Power BI dashboard? You are in the right place!
I am a skilled Data Analyst proficient in handling complex relational databases and messy datasets. Whether you have multi-table data that needs cleaning, relational schemas that require SQL Server optimization, or raw CSV/Excel files that need a corporate dashboard, I deliver clear, actionable business insights.
My Expertise Includes:
Data Cleaning & Wrangling: Handling missing values, removing duplicates, and data formatting using Python (Pandas/NumPy).
SQL Database Queries: Writing advanced SQL scripts to query data, join tables, and extract key trends in SSMS.
Exploratory Data Analysis (EDA): Uncovering hidden patterns and distributions using Seaborn and Matplotlib.
Interactive Power BI Dashboards: Designing clean, executive-level charts, KPI cards, and trend reports.
Tools I Use Fluently:
SQL Server Management Studio (SSMS)
Python (VS Code, Jupyter Notebooks)
Power BI Desktop
Advanced Excel
Every dataset has a unique story. Please drop me a message with your data and requirements.
Analysis type:
Descriptive Analysis
•
Other
Expertise:
Business Insights
Technology:
Excel
•
Power BI
•
Other
Programming language:
Python
•
SQL
FAQ
Do I need to provide clean data?
Not at all! I specialize in data cleaning. You can hand over your raw, messy CSV files, Excel sheets, or SQL databases, and I will handle all the cleaning, duplicate removal, and missing values for you.
Which tools do you use for analysis and visualization?
I use SQL Server Management Studio (SSMS) for querying databases, Python (Pandas, NumPy, Seaborn) in VS Code/Jupyter Notebooks for data cleaning and exploration, and Power BI Desktop for creating interactive dashboards.
Can you work with large, complex datasets with multiple tables?
Yes, absolutely. I am fully comfortable handling relational databases, joining multiple data tables (like connecting customers, orders, payments, and reviews), and ensuring data integrity before building insights.
