A Scalable Data Engineering Solution
By Hijir Della Wirasti
Project Overview
This project was conducted as part of a Data Engineering initiative with ID/X Partners, focusing on Data Warehouse Development, ETL Optimization, and SQL Analytics using MSSQL and Talend. The goal was to enhance data integration and streamline reporting for a financial services client by implementing efficient data pipelines and automation.
Background & Problem Statement
A banking sector client working with ID/X Partners faced challenges in managing data extraction from multiple sources, including Excel, CSV, and SQL Server databases. These disparate data sources contained crucial financial and customer records, but their fragmented nature led to:
- Data inconsistency and redundancy across reports
- Delays in analytics and decision-making
- Inefficient data retrieval for stakeholders
Project Objectives
To address these challenges, I developed a centralized and automated data processing system with the following key objectives:
✔️ Integrate multiple data sources into a unified Data Warehouse
✔️ Optimize ETL workflows for real-time data updates
✔️ Enhance SQL query performance to enable faster reporting
Solution Implementation
1️⃣ Data Warehouse Architecture
A structured Data Warehouse (DWH) was designed with:
📌 Dimension Tables – DimCustomer, DimAccount, DimBranch
📌 Fact Table – FactTransaction to store transactional data
📌 Schema Optimization – Establishing primary and foreign key relationships
2️⃣ ETL Pipeline Development with Talend
A robust ETL (Extract, Transform, Load) pipeline was built to ensure efficient data processing:
🔹 Data Sources: Integrated data from SQL databases, Excel, and CSV files
🔹 Data Transformation: Cleaned, standardized, and formatted data for consistency
🔹 Duplicate Removal: Ensured unique transactions to eliminate redundancy
🔹 Automated Scheduling: Orchestrated real-time data updates to improve efficiency
3️⃣ SQL Stored Procedures for Analytics
To enhance data retrieval and reporting efficiency, two key SQL Stored Procedures were developed:
📊 DailyTransaction – Aggregates daily transaction counts and amounts
💰 BalancePerCustomer – Computes customer account balances based on transaction history
Challenges & Learnings
💡 Complex Data Merging – Integrated diverse data formats into a single, seamless pipeline
💡 Performance Optimization – Ensured efficient query execution through indexing & optimized joins
💡 Real-World ETL Workflow – Mastered Talend for scalable data processing
Results & Impact
🚀 Improved Data Processing Speed – Reduced reporting delays significantly
📈 Enhanced Data Consistency – Eliminated redundancies in financial records
✅ Scalable & Automated Solution – Designed an end-to-end ETL system for ongoing data updates
Conclusion
This project for ID/X Partners demonstrates expertise in Data Engineering, ETL Pipeline Development, and Data Warehouse Optimization to improve business intelligence and analytics. The successful implementation of SQL, Talend, and MSSQL highlights the ability to design scalable and automated data solutions for enterprise use.