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Customer 360 View for a Leading Private Bank",{"rendered":506,"protected":507},"\n\u003Cp>Global private banks operate across multiple regions, each running its own information system. When customer data lives in silos, the ability to deliver consistent, compliant, and personalized services breaks down. This is the situation our client faced—and the reason we collaborated to build a unified, governed data platform that gives every business team a complete view of their customers.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cem>Big Data  •  Customer 360  •  Global Data Platform  •  Private Banking  •  Data Lake Governance  •  Data-as-a-Service  •  Advanced Analytics\u003C\u002Fem>\u003C\u002Fp>\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"h-context-and-challenges-fragmented-regional-systems-hiding-the-full-customer-picture\">Context and Challenges: Fragmented Regional Systems Hiding the Full Customer Picture\u003C\u002Fh2>\n\n\n\u003Cp>Our client is a global private bank with operations spanning every major region. Each regional entity manages its own information system, leading to a fragmented technology landscape with no shared infrastructure for customer data.\u003C\u002Fp>\n\n\n\n\u003Cp>This fragmentation has a direct impact on the bank’s ability to serve its clients. Customers enrolled across multiple regions are managed as separate records, with no consolidated view available to business departments. The consequences reach across critical processes:\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>Portfolio management\u003C\u002Fli>\n\n\n\n\u003Cli>Client onboarding\u003C\u002Fli>\n\n\n\n\u003Cli>Fraud detection and Anti-Money Laundering (AML)\u003C\u002Fli>\n\n\n\n\u003Cli>Know Your Customer (KYC) and Customer Due Diligence\u003C\u002Fli>\n\n\n\n\u003Cli>Investment recommendations\u003C\u002Fli>\n\n\n\n\u003Cli>Marketing analytics\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\n\u003Cp>Without a single source of truth for customer data, the bank could neither optimize its service quality nor meet the full scope of its compliance obligations. Our client needed a global, consolidated view of customer data to address these challenges—and to create the foundation for smarter, faster decision-making across all regions.\u003C\u002Fp>\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"h-our-approach-building-a-governed-global-data-platform-to-unify-customer-intelligence\">Our Approach: Building a Governed Global Data Platform to Unify Customer Intelligence\u003C\u002Fh2>\n\n\n\u003Cp>To meet our client’s expectations, we took charge of implementing a global data platform built on the Hortonworks technology stack, including a governed data lake at its core. Our work unfolded across five key steps.\u003C\u002Fp>\n\n\n\n\u003Col class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>Data-as-a-Service via REST API. \u003C\u002Fstrong>To make the platform’s data accessible at scale, we developed a Data-as-a-Service solution through a REST API. This interface allows every system across the organization to consume customer data efficiently and consistently, regardless of where it operates.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Stakeholder discovery across regions. \u003C\u002Fstrong>We started by interviewing application and product owners across the different countries, covering both functional and technical dimensions. This discovery phase gave us a clear picture of the existing data landscape, regional specificities, and the gaps that the platform would need to bridge.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Data lake infrastructure and data ingestion. \u003C\u002Fstrong>We built the complete data lake infrastructure and uploaded customer data from all regions into it. This central repository became the single source of truth for all customer information across the organization.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Dedicated data marts for high-performance distribution. \u003C\u002Fstrong>On top of the data lake, we created dedicated data marts—including Finance and Customer marts—to ensure high-performance data distribution to the business teams that needed it most.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Data catalog and governance layer. \u003C\u002Fstrong>We implemented a data catalog to enable proper knowledge and governance of data across all regions. We also introduced a data masking security layer to anonymize data based on user access profiles—ensuring that sensitive information is protected while remaining accessible to authorized users.\u003C\u002Fli>\n\u003C\u002Fol>\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"h-key-benefits-from-siloed-data-to-a-360-degree-view\">Key Benefits: From Siloed Data to a 360-Degree View\u003C\u002Fh2>\n\n\n\u003Cp>The platform delivered measurable improvements across four dimensions.\u003C\u002Fp>\n\n\n\n\u003Cul class=\"wp-block-list\">\n\u003Cli>\u003Cstrong>New data-driven and advanced analytics capabilities: \u003C\u002Fstrong>The platform opened the door to capabilities that were previously out of reach. Business processes such as client onboarding, customer due diligence, and investment recommendations are now informed by reliable, centralized data. Beyond operational improvements, the bank has also deployed machine learning use cases in Finance and Marketing, marking a meaningful step toward a data-driven culture.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>A consolidated 360-degree customer view: \u003C\u002Fstrong>For the first time, business teams have access to a unified view of customer data across all regions. This consolidation directly improves the accuracy and effectiveness of core business processes, from portfolio management to investment recommendations.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Reduced data integration time and cost: \u003C\u002Fstrong>With all data accessible in one central repository, the bank has significantly reduced the time and cost associated with data integration. Teams no longer need to reconcile information across disconnected regional systems.\u003C\u002Fli>\n\n\n\n\u003Cli>\u003Cstrong>Full data visibility and governance: \u003C\u002Fstrong>Functional and business metadata—including data lineage—is now available for all data elements in the lake. This visibility gives data owners and compliance teams the confidence that data is well-understood, traceable, and governed appropriately.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"team-involved\">Team Involved\u003C\u002Fh2>\n\n\n\u003Cp>This project was delivered by a cross-functional team of 1 Solution Architect, 2 Business Analysts, and 5 Data Engineers, who collaborated closely with our client over 24 months. Their combined expertise in data architecture, business analysis, and engineering was key to delivering a platform that meets both technical and operational requirements at a global scale.\u003C\u002Fp>\n\n\n\u003Ch2 class=\"wp-block-heading\" id=\"h-technologies-used\">Technologies Used\u003C\u002Fh2>\n\n\n\u003Cp>\u003Cstrong>Hortonworks: \u003C\u002Fstrong>Provided the core technology stack for building and managing the governed data lake infrastructure.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Apache Spark: \u003C\u002Fstrong>Used for large-scale data processing and transformation across distributed datasets.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Apache HBase: \u003C\u002Fstrong>Enabled low-latency access to large volumes of structured customer data.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Apache Hive: \u003C\u002Fstrong>Supported data warehouse capabilities on top of the data lake for structured querying.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Apache Atlas: 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