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Data Analysis Projects

Overview

These projects focuses on data analysis using multiple tools and techniques to derive insights from various datasets.

The goal 🎯 is to explore 📈 , visualize 📊 and interpret data to support decision-making processes.

Tools Used:

✅ Google Sheets – For quick data analysis and reporting.

✅ SQL – For querying and managing structured databases.

✅ BiqQuery - A fully managed, serverless data warehouse by Google Cloud that enables fast SQL queries and large-scale data analysis.

✅ Looker Studio – For web-based data visualization.

✅ Tableau – For interactive data visualization and dashboards.

✅ Amplitude - A product analytics platform that helps teams track user behavior, analyze engagement, and make data-driven decisions.

✅ Python (Pandas, NumPy, Matplotlib, Seaborn) – For data manipulation, analysis, and visualization.

✅ A/B testing to compare different versions of a feature or treatment and analyze the impact on user behavior or performance.

Project Components

  1. Data Collection - Collect data from multiple sources such as CSV files, databases, and APIs.

  2. Data Cleaning and Preprocessing - Handle missing values, remove duplicates, and structure data for analysis.

  3. Exploratory Data Analysis (EDA) - Use statistical summaries and visualizations to understand data patterns.

  4. Data Visualization - Create charts, graphs, and dashboards to present key insights.

  5. Insights & Decision Making - Interpret results and provide data-driven recommendations.

How to run:

  1. Clone the repository:

git clone https://github.com/VitaliiKalyta96/Data-analysis.git

  1. Open any project in folder.

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These projects are about data analysis using multiple tools and techniques to derive insights from various datasets.

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