Accelerate Digital Transformation with Data Virtualization in Banking, Financial Services, and Insurance (US)
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The webinar discusses how data virtualization accelerates digital transformation for banks, especially post-COVID, highlighting the need for omnichannel integration, agile data access, and operational efficiencies. Key technology trends include robotic process automation, a universal data access layer, and enhanced data governance. Wipro shared success stories showcasing how data virtualization transformed operations for clients, leading to real-time data access and improved decision-making capabilities.
Accelerate Digital Transformation with Data Virtualization in Banking, Financial Services, and Insurance (US)
- 1. Public Data Virtualization Webinar – Accelerate digital transformation with data virtualization
- 2. Public © confidential 2 Speakers today Jeevan Jambhulkar Director, Data, Analytics & AI, Wipro Paul Moxon SVP Data Architectures & Chief Evangelist, Denodo
- 3. Public © confidential 3 Post-COVID Priorities for Banks Revenue Generation • Omnichannel integration for 360° view of customer • Frictionless digital on-boarding • Open Banking for all-encompassing approach to customer engagement Cost Management • Increased use of AI for decision making • Operational efficiencies through digitalization Regulatory Compliance • Managing regulatory compliance costs
- 4. Public © confidential 4 COVID-19 – Accelerating the Trends Digital transactions increased by 20% • Mobile and online • Accelerating ongoing changes in banking distribution channels Physical branches – Essential services, but… • Reduced hours and visits by appointment Multichannel integration and cross-channel CX is critical • Customers need and use all channels • Mobile, online, branch, call center, etc.
- 5. Public © confidential 5 The Need for Agile • Black Swan or not…the pandemic has highlighted many challenges e.g. • Employee access to needed data when working remotely • Small business loan programs overwhelmed systems • UK Job Retention Scheme (Furlough Scheme) • US Paycheck Protection Program • Manual processing ‘broken’ due to staff shortages • Need for unified multichannel engagement with customers • Breaking down silos between products
- 6. Public © confidential 6 Technology Trends – The ‘New Normal’ 1 Delivering multichannel experience to customer • Integrating the customer data across product silos • Customer 360, KYC, etc. 2 Increased use of Robotic Process Automation (RPA) • Automating manual processing • Exceptions escalated to person for analysis 3 Universal data access layer – Data Fabric • Access from anywhere…to anything (with security) 4 Dynamic data access – no code/low code
- 7. Public © confidential 7 Technology Trends – The ‘New Normal’ Governance Empower employees within parameters to protect the organization from risk Mandate Broker and orchestration with focus on innovation Process Fluid and iterative assemble-to- order approach Architecture Secure integration fabric with architectural guardrails and guidance Mandate broker of services Mandate broker of services IDEATE ASSEMBLE CONSUME INTEGRATION FABRIC Robotics process automation End user Computing Traditional data center Applications CYBERSECURITY Organization Professional services organization with versatile generalists Private Managed Public Cloud API H H H Source: Financial Services Technology 2020 and Beyond: Embracing Disruption, PwC
- 8. Public © confidential 8 Data Virtualization – A Data Fabric Layer “Data virtualization integrates disparate data sources in real time or near-real time to meet demands for analytics and transactional data.” – Create a Road Map For A Real-time, Agile, Self-Service Data Platform, Forrester Research, Dec 16, 2015 Consume in business applications Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users DATA CONSUMERSAnalytical Operational Multiple Protocols, Formats Query, Search, Browse Request/Reply, Event Driven Secure Delivery Combine related data into views CONSUME Share, Deliver, Publish, Govern, Collaborate COMBINE Discover, Transform, Prepare, Improve Quality, Integrate CONNECT Normalized views of disparate data SQL, MDX Web Services Big Data APIs Web Automation and Indexing Connect to disparate data sources Databases & Warehouses, Cloud/Saas Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word... DISPARATE DATA SOURCESMore Structured Less Structured 3 2 1
- 9. Public © confidential 9 How Does It Work? Development Lifecycle Mgmt Monitoring & Audit Governance Security Development Tools and SDK Scheduled Tasks Data Caching Query Optimizer Mobile, Web, UsersEnterprise application, ESB Reporting, BI, Portals Databases & warehouses Enterprise applications Cloud/SaaS applications XML, Excel, Flat Files Big data NoSQL Collaboration Web 2.0 PDF, Docs, Index, Email Base View Base View Base View Base View Base View Base View Abstraction Base View Data Source Layer Derived View Derived View Unified View Unified View Unified View Unified View Customer360 View Data Mart View Application Layer Business Layer Transformation & Cleansing J J J S J A JU JDBC/ODBC/ADO.Net SOAP/REST WS
- 10. Public © confidential 10 Data Virtualization Connects the Users to the Data That They Need Data Virtualization allows you to connect to (almost) any data source You can combine and transform that data into the format needed by the consumer The data can be exposed to the consumers in a format and interface that is usable by them • Typically consumers use the tools that they already use – they don’t have to learn new tools and skills to access the data All of this can be done without copying or moving the data • The data stays in the original sources (databases, applications, files, etc.) and is retrieved, in real-time, on demand
- 11. Public © confidential 11 Example Use Cases Apps/API Sales HR Marketing Data Science AI/ML Executive DATA VIRTUALIZATION LAYER Data Consumption Self-Service Analytics Real-time Decisions Data Science (ML & AI) Data Marketplace K.Y.C. (Customer 360) Compliance (IFRS17, GRC) Mergers & Acquisitions Apps (Mobile & web) Data Governance, Manipulation & Access Agility & Simplicity Semantic Layer Data Abstraction Real-time Delivery Zero Replication Sophisticated Optimizations Data Governance Data Security Data Storage & Management Data Integration Logical Data Warehouse Hybrid Data Fabric Enterprise Data Fabric Cloud Modernization APIfication (& SQLification) Refactoring & Replatforming From Data Storage & Management, to Data Consumers, going through Data Governance & Security
- 12. Public © confidential 12 Poll Question: Which of the following is closest and most relevant to your current data integration, analytical and business operation needs? Hybrid & multi-cloud use cases : real-time data integration and access across the enterprise landscape for analytics purpose Logical Data Warehouse : Data integration, access from the traditional data warehouses and new age data warehouses / data lakes across the enterprise Real-time integration of internal and external data sources and systems for business consumption applications / BI Tools Real-time integrated view of enterprise data across multiple source systems / OLTP systems for business operations Mergers and Acquisitions initiative : Real-time data integration to build single view of business data from business entities/companies (or) Data integration and access from multiple transactional apps due to acquisitions or group companies 1 2 3 4 5
- 13. Public © confidential 13 A Glimpse of how we helped our Customers with successful Data virtualization Implementation Success Story - For a leading medical device manufacturer in US Business & IT drivers: • Daily company wide sales report delayed by 24 to 48 hours & Delayed management reporting • Business & customer data stored in multiple ERP, CRM systems and legacy applications • Integrating data from different sources (on premise and cloud) • Providing ad-hoc access to the data lake for business users How Wipro Helped: • Build data fabric using Denodo to link machine learning, ad-hoc analytics and visualization to source data systems • Data delivered through the fabric, to consumers, by web services • Data from different system harmonized in Denodo with canonical models • Unified data platform ensures visibility to CRM and ERP systems & integrated reporting/analytics capability Solution highlights: • Denodo enabled unified data platform across multiple CRM & DB’s • Near real time access (< 2 hours) to data • Finance could publish consolidated sales reports to management on same business day • Centralized data governance and security through the unified layer of Denodo • 50%-time savings over traditional ETL projects
- 14. Public © confidential 14 Success Story – Architecture Roadmap End-to-end Business Processes Source Systems Map to Business Functions Data Virtualization Unified Data Platform Data Catalog Data Governance Data Access Data Fabric/Business Semantic Layer Product Lifecycle Management Hire to Retire Record to Report Source to Pay IT Strategy to Operations Market to Opportunity Quote to Cash Plan to Forecast Plan to Deliver
- 15. Public © confidential 15 Data Virtualization - Lessons Learned Best Fit Use-cases • Real time data access • Self-service data exploration • Real-time query optimization • Read and write back • Data Blending • Data Federation • Data Masking & Data Quality • Data Governance • On-Premise to Cloud Pitfalls • Not an ETL replacement • Not ideal for multi-pass data cleansing • Need customization for Marketplace use cases Misconceptions • It is not ETL • It is not Data Visualization • It is not a physical database
- 16. Public © confidential 16 • Extensive usage for Regression test execution facilitating DevOps, CICD methodologies • 100% Data validation with complete coverage on Test cases, test execution, data • Batch execution – Scheduler to trigger test execution with no manual intervention Wipro’s transformation tool • Identification of Integration patterns to automate Integration creation in bulk • Provides UI to configure & operate • Design pattern based approach to automate the development • Analysis & migration • Reference Architecture • Implementation approaches • Review check list • Learnings, Possible mitigation options • Common problems, solutions • Re-usable frameworks Customer 360 • Leveraged Banking Customer Data Model • Leverage Communication Customer Data Model Asset 360 • Leverage Asset Data Model Leverage Wipro’s in-house accelerators and frameworks for speed up delivery NextGen DI™ Cook BookUnified Framework Smart Data Validation
- 17. Public © confidential 17 Data Landscape Modernisation – Wipro’s experience and capabilities Appliances, Data Warehouse ERP based BW Modernization Data Marts & Enterprise Data Warehouses Third Normal or De normalized EDWs ERP Based Business Warehouses CDRS SmartPro NextGen DI IQNxt Compiler Works IntelliProc BD2DB Wipro can help you unshackle and achieve “Data Modernization” by focusing on 3 key areas Migrating from as-is state to to-be state leveraging Wipro tools and accelerators As-is State To be State Accelerators Upgrade to on- premise databases Cloud selection – IaaS, SaaS, PaaS Database Freedom OLTP Application DBs Structured data Metadata: Tables, Views, Schemas etc. Digital Database Modernization NoSQL, Grab DB Metadata: Tables, Views, Schemas etc. Reduction in Data Centers and IT Services up to 80% Build new business functionality FASTER 3-5x Annual OPEX reduction up-to 80% Increase in speed by 2-3x 3 year TCO cost saving up-to 92%
- 18. Public © confidential 18 Multi-Cloud Integration with Data Virtualization BigQuery Google Cloud Storage Snowflake Amazon RDS Amazon Elastic Amazon Redshift S3 Azure SQL HDInsights On-Prem Data Centre Manage cloud and on-premises security from a single point Track cloud usage by department or individual. Enable migrations from on-premises to cloud sources, with no impact on day-to-day operations Scale the solution only as needed, to hold down costs Integrate data from silos within data lakes, from cloud and on-premises sources simultaneously, from SaaS applications, and other sources, without replication, in real time Reduce the inherent latency of accessing data from network sources
- 19. Public © confidential 19 Data Marketplace - Context Data Marketplace is a “shopping interface” where data services are presented which can be used by data users, to find best-fit data that meet their needs. It enables better business and technology collaboration Simple platform that obtains data from across the Ecosystem Curation: it selects and qualifies data sets, describes each data set, and collects and manages metadata about the collection and each individual data set Creating a faster, easier way to find and access data Categorization: It organizes the marketplace to simplify browsing. Example, a researcher seeking health data doesn't need to browse through unrelated data sets about customers, employees, or other data Cataloguing: It exposes data sets for data shoppers, including descriptions and metadata. It is a view into the inventory of curated data sets. Rich metadata and powerful search are important catalogue features Confidentiality: Data consumers actively participate in reporting any anomalies in cataloguing, curating, and categorizing data. It continuously improves the quality and value of the available data Solution principles • Design-led Agile Approach • User based Designed UX/UI • Accurate, Relevant Data-sets • Designed Data Flows, Info Architectures • Metadata tagged Data • Relevant Search • Crowdsourced Insights User & business driven service design • Intuitive Searches • Platform that leverages APIs and Microservices Toolkits • Data Security and Access Management Rules • Interfacing with Multiple Tools Data & platform Underpinning • Business Analyst • Data Science Experts • User-driven Collaboration Community
- 20. Public © confidential 20 Data Marketplace - Architecture Data Consumers Data Marketplace PortalSources Database, Enterprise Data Warehouse Enterprise Application Data DV Layer Publish Data Services Combine Transform, Mashup Data Catalog Governance Optimizer Cache Metadata Schedule Security Views Data catalog Enterprise datasets Data viewing Access management Collaboration, sharing End Users Business Analysts Reports / dashboards
- 21. Public © confidential 21 Q A
- 22. Public Thank you for your time. Denodo Datafest was a great Success. Embed intelligence within your organizations with our joint solution offering. Reach out to below address to schedule a demo and discovery session Ask.analytics@wipro.com