You will get I will analyze, visualize and interpret your data
Project details
I will clean and analyze your raw dataset and provide a comprehensive summary in Excel or Python.
Includes 3 questions answered about your dataset.
I will also create a dynamic Power BI or Excel dashboard featuring interactive visuals, charts, and filters for deeper data insights.
I’m here to help you uncover valuable trends and provide actionable insights. I’m an aspiring data scientist with a strong foundation in business analysis, and I specialize in turning complex data into clear, understandable visuals and models. Let’s take your data to the next level!
Includes 3 questions answered about your dataset.
I will also create a dynamic Power BI or Excel dashboard featuring interactive visuals, charts, and filters for deeper data insights.
I’m here to help you uncover valuable trends and provide actionable insights. I’m an aspiring data scientist with a strong foundation in business analysis, and I specialize in turning complex data into clear, understandable visuals and models. Let’s take your data to the next level!
Database Type
MySQL, PostgreSQLWhat's included
| Service Tiers |
Starter
$25
|
Standard
$50
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 8 days |
Number of Revisions | 1 | 1 | 2 |
Source Code | - |
About Peremobo
Data Scientist
Lagos, Nigeria - 8:00 am local time
Steps for completing your project
After purchasing the project, send requirements so Peremobo can start the project.
Delivery time starts when Peremobo receives requirements from you.
Peremobo works on your project following the steps below.
Revisions may occur after the delivery date.
Initial Consultation & Requirement Gathering
Understand the client’s goals and objectives. Discuss the data sources, desired outcomes, and expectations. Clarify any specific KPIs, business metrics, or data points that need to be analyzed. Define the project timeline.
Data Collection and Preprocessing
Collect data from the provided sources. Clean and preprocess the data, e.g, handling missing values, data normalization, and outlier detection. Perform exploratory data analysis (EDA) to understand data distributions, patterns, and trends.