CASE STUDY
Enterprise Data Platform Modernization – FinServ Case Study
Introduction
This case study explores the successful collaboration between Hoonartek and a leading private sector bank with a strong history of innovation in the financial services industry. The Client has consistently demonstrated a commitment to technological advancement, pioneering digital banking initiatives and fostering a customer-centric approach. With a growing customer base and a diverse range of financial products and services, the Client recognized the critical need to modernize its data infrastructure to support its continued growth and enhance its competitive advantage in the global marketplace.
Faced with the challenges of a rapidly evolving business landscape and the need for data-driven decision-making, the Client recognized the critical need to modernize their existing data infrastructure. Their legacy data warehouse, constrained by limited scalability, slow query performance, and data quality issues, was no longer adequate to support their growing business needs.
The Business Challenge
The Client’s existing data environment presented several significant hurdles:
Real-time Data Ingestion Limitations: The inability to ingest data in real-time resulted in delayed decision-making, missed opportunities, and hindered responsiveness to market changes and customer demands.
Unstructured and Social Media Data Management: Difficulty in efficiently managing diverse data formats, including unstructured and social media feeds.
Data Silos: Data was fragmented across various systems and departments, hindering a unified view of customer, financial, and operational data.
Slow Data Access: Slow query performance and long wait times for critical insights impeded timely decision-making across the organization.
Limited Scalability: The existing on-premises infrastructure lacked the scalability and flexibility to accommodate the growing volume and velocity of data, hindering future growth and innovation, especially with a projected data volume exceeding 1.5 PB.
Data Governance Issues: Inaccurate and inconsistent data across various sources impacted the reliability of business intelligence reports and analytics.
Compliance and Security Risks: The lack of robust data security measures and compliance with evolving global regulations (e.g., GDPR) posed significant risks to the organization.
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Joint Solution Discovery & Implementation Plan
Recognizing the urgency of addressing these challenges, the Client sought a partner with expertise in data warehousing and cloud technologies. Hoonartek was selected for the proven track record of successful data modernization projects and our deep understanding of the financial industry.
The engagement commenced with a thorough assessment of the Client’s existing data landscape, including data sources, data volumes, data quality, and business requirements. Through a series of workshops and collaborative discussions, Hoonartek gained a deep understanding of the Client’s business objectives and identified key areas for improvement.
Based on these insights, a comprehensive data modernization roadmap was developed. This roadmap outlined a phased approach to:
Cloud Migration: Migrate the existing data warehouse to the Microsoft Azure cloud platform, leveraging its scalability, performance, and cost-effectiveness.
Data Ingestion and Transformation: Implement a robust data pipeline using Azure Data Factory (ADF) to efficiently ingest data from over 120 source systems and 3100+ data feeds, including databases, applications, and flat files.
- Establish a data lake architecture to store and process both structured and unstructured data.
- Integrate Oracle GoldenGate (OGG) and Azure Event Hubs to enable real-time data streaming and near real-time analytics.
- Develop custom data transformation logic using PySpark on Databricks to handle complex data formats, such as CB XML files.
Data Quality and Governance: Implement a comprehensive data quality framework, including data profiling, cleansing, and validation rules, to ensure data accuracy and consistency. This involved defining over 5400+ Critical Data Elements (CDEs) and establishing 4133 DQ Rules.
- Implement data lineage tracking to understand the origin and transformations of data, enhancing data traceability and accountability.
- Integrate Alation for data cataloging, metadata management, and business glossary, empowering data consumers to easily discover, understand, and trust data.
Data Security and Compliance: Implement robust security measures, including encryption, access controls, and data masking, to protect sensitive data with over 3 thousand PIIs identified.
- Ensure compliance with relevant data privacy regulations, such as GDPR and other global and regional data protection laws.
DevOps and Monitoring: Implement DevOps best practices, including continuous integration and continuous delivery (CI/CD), to accelerate development and deployment cycles.
- Integrate Applogic for real-time application performance monitoring and proactive issue resolution.
Industry Perspective
This project exemplifies the increasing importance of data-driven decision-making in the global financial services sector. By leveraging cloud technologies, modern data warehousing principles, and a focus on data quality and governance, with Databricks playing a key role in enabling efficient data processing, Hoonartek helped the Client gain a competitive edge in a rapidly evolving market.
Outcomes
Enhanced Data-Driven Decision Making & Accessibility:
Reduced query response times enabled faster, informed decisions across 20+ departments. The cloud platform facilitated scalability, accommodating future growth, and supported an enterprise data model with 40+ subject areas, 400+ entities, and 18000+ attributes.
Improved Data Quality & Reliability:
Enhanced data accuracy and consistency across the enterprise resulted in reliable insights and reduced risk. Data remediation, like updates to customer due diligence for 6 million+ customers, contributed significantly.
Strengthened Data Security & Compliance:
Robust security measures and data governance ensured compliance with global/regional regulations, minimizing data breach risks. Over 3 thousand PIIs were identified and secured.
Optimized Operational Efficiency & Cost Reduction:
Streamlined data management, automating 350+ manual processes, reduced operational overhead. Cloud-based storage and processing resulted in optimized costs. Architecture modernization, workload segmentation, and automation further drove efficiency.
Conclusion:
The successful implementation of this enterprise data platform modernization project demonstrates the value of partnering with Hoonartek to address complex data challenges. By combining deep industry expertise with cutting-edge technologies like Databricks, we empowered the Client to unlock the true value of their data assets, drive business growth, and gain a competitive advantage in the marketplace.
To learn how Hoonartek can help your organization overcome similar data challenges, unlock the true value of your data, and drive significant business outcomes, schedule a free consultation with our data experts today. We’ll discuss your specific needs and explore how our data-driven solutions can help you achieve your business goals.
