Business Intelligence and Data Warehousing

Table of Contents

1. Overview
2. Key Features
3. Repository Structure
4. Analysis of KPIs and Insights
5. Implications for Business Decision-Making
6. Note on Compatibility

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Overview

This repository contains resources related to a Business Intelligence (BI) and Data Warehousing (DWH) project. It includes scripts, data files, and analysis results used to set up and analyze the DWH environment and derive Key Performance Indicators (KPIs).

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Key Features

• Architecture: Architecture variant to suit the specific business needs.
• ETL Processes: ETL processes using Talend for data integration and transformation.
• KPI Derivation: Derive Key Performance Indicators (KPIs) to measure and evaluate business performance.

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Repository Structure

• Data_Marts: Contains SQL scripts related to the Data Marts.
• Data_Sources: Includes SQL scripts for creating databases, along with CSV and JSON files generated from Python scripts for testing purposes.
• KPIs: Features SQL script screenshots and analysis of Key Performance Indicators (KPIs).
• Python_Simulated_Data: Python scripts for populating databases and generating CSV and JSON files with simulated data.
• Talend: Screenshots related to ETL processes in Talend.
• Architecture.png: Displays an image file depicting the architecture proposed.

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Analysis of KPIs and Insights

1. Average Revenue per Transaction KPI: With an average revenue per transaction of $5625.7580, we can assess the financial health of the organization and identify opportunities for revenue growth.
2. Conversion Rate by Lead Source KPI:
   • Email: 0.2549
   • Social Media: 0.2379
   • Website: 0.2434 These conversion rates indicate the effectiveness of different lead sources in converting prospects into customers. Email campaigns appear to have the highest conversion rate, followed by website and social media channels.
3. Average First Response Time (FRT) KPI: The average first response time is calculated to be approximately 35.1067 days. This metric measures the efficiency of the customer support team in addressing customer inquiries and issues in a timely manner.

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Implications for Business Decision-Making

• Based on the ART KPI, we can identify products or services with high transaction values and prioritize marketing efforts or product enhancements accordingly.
• The insights from the Conversion Rate by Lead Source KPI can guide marketing strategies and budget allocation towards channels that yield the highest conversion rates, such as email campaigns.
• Analyzing the FRT KPI can help optimize customer support processes, allocate resources effectively, and improve overall customer satisfaction.

These insights can inform strategic decisions, drive operational improvements, and ultimately contribute to the organization's success.

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Note on Compatibility

• The Data Marts and Databases scripts are optimized for MySQL Workbench. Using other database management systems may require adjustments.
• To install MySQL Workbench visit the official MySQL Workbench website.