Understanding Cloud-Native Data, Fintech Security, and AI in Banking

An essential guide for Banking CXOs on cloud-native data, a cornerstone of banking digital transformation. Learn core concepts, including Fintech security and AI in banking, to drive business value, enhance banking analytics, achieve operational excellence, and navigate the evolving regulatory landscape.

Introduction: The Data Revolution, Cloud Adoption in Financial Services, and the Cloud-Native Imperative for Banking CXOs

The banking sector confronts an unprecedented data surge, making cloud adoption essential. Banking CXOs face the critical challenge of transforming this deluge into actionable intelligence to boost customer experiences, fortify risk management, streamline operations, ensure compliance, and drive innovation. Traditional on-premises infrastructures, often rigid and costly, impede these goals and hinder advanced analytics like AI/ML. Consequently, Cloud-Native Data emerges as a strategic imperative—a fundamental shift to systems architected for cloud agility and scalability—empowering leaders to guide their institutions toward data-driven excellence, regulatory nimbleness, and sustained competitive advantage. 

Key considerations in this landscape include: 

• The Core Challenge: Data Deluge & Legacy Constraints
  • Navigating a massive influx of diverse data from sources, including transactions, customer interactions, market feeds, regulatory reports, fraud detection, and KYC information.
  • Overcoming the limitations of traditional on-premises data infrastructures, which are often rigid, expensive, and struggle to support modern analytical demands, thereby preventing innovation.
• The CXO Mandate: Driving Value from Data
  • The critical leadership task is to convert vast data volumes into actionable intelligence to achieve strategic business outcomes.
• The Strategic Solution: Adopting Cloud-Native Architecture
  • Embracing a fundamental paradigm shift by architecting data systems specifically to harness the full power, scalability, and agility of cloud computing, moving beyond simply migrating existing databases.
• Achievable Outcomes & Sustained Advantage:
  • Enhanced Operations & Innovation: Delivering superior customer experiences, achieving greater operational efficiency, and fostering the development of innovative financial products.
  • Robust Governance & Agility: Ensuring strong risk management practices and adaptable, efficient regulatory compliance.
  • Market Leadership: Securing data-driven excellence and a lasting competitive edge in an increasingly digital marketplace. 

This guide provides a foundational understanding of cloud-native data, especially tailored for banking CXOs, focusing on core concepts and their direct impact on delivering tangible business value. 

What is “Cloud-Native Data”? Demystifying Core Concepts for Banking Cloud Strategy

The term “cloud-native” describes an approach to building and running applications that fully leverages the advantages inherent in the cloud computing delivery model. When applied to data, this means designing and implementing data systems specifically for cloud environments rather than merely adapting legacy systems—a key component of an effective banking cloud strategy. 

Key Characteristics of Cloud-Native Data Architectures: Scalability, Resilience, and Agility for Modern Banking 

• Scalability & Elasticity: Mastering Peak Loads and Optimizing Banking Cloud Costs
  • Concept: Systems can automatically and dynamically scale resources (compute power, storage) based on real-time demand. For instance, a banking system can seamlessly handle surges in online transaction volumes during month-end payroll processing or peak trading activity and then scale back down to optimize costs. It addresses key scalability patterns.
  • CXO Implication: Pay-as-you-go models significantly reduce wasted expenditure on over-provisioned infrastructure, optimizing Total Cost of Ownership (TCO). It ensures high performance and availability during critical periods like market volatility or promotional campaigns without manual intervention or excessive upfront investment.
• Resilience & High Availability: Ensuring Business Continuity and Banking Service Reliability
  • Concept: Systems are architected for inherent fault tolerance. If one component or server experiences an issue, the system automatically recovers or redirects operations, ensuring continuous service. Data is frequently replicated across multiple geographically distinct availability zones to protect against regional outages, crucial for service reliability.
  • CXO Implication: Minimizes downtime for critical banking applications such as online banking portals, payment gateways, trading platforms, and ATM networks. It ensures business continuity, maintains customer trust, safeguards reputation, and mitigates financial and regulatory risks associated with service interruptions.
• Agility & Speed: Accelerating Financial Product Innovation and Regulatory Response via Cloud
  • Concept: Enables the rapid development, deployment, and iteration of data services, analytical applications, and new financial products. It is often achieved through DevOps practices, microservices architecture, and containerization technologies.
  • CXO Implication: Faster time-to-market for new digital banking products and services (e.g., new mobile banking features, personalized loan offerings). Quicker deployment of analytical models for fraud detection, credit scoring, or customer segmentation. Enhanced ability to rapidly respond to evolving market dynamics, competitive pressures, or new regulatory mandates (e.g., changes in reporting standards).
• Service-Based & API-Driven: Enabling Open Banking, Fintech Integration, and Microservices Architecture
  • Concept: Data and functionalities are exposed as well-defined, independent services (often microservices) accessible via Application Programming Interfaces (APIs). It fosters modularity, reusability, and interoperability between various systems and applications, supporting Open Banking and a microservices architecture.
  • CXO Implication: Facilitates easier integration with third-party applications (e.g., FinTech partners, payment networks), partner ecosystems (e.g., for Open Banking initiatives), and internal legacy systems. It promotes innovation by allowing different development teams to work independently on specific services, accelerating the creation of a connected banking ecosystem and enabling compliance with Open Banking regulations like PSD2. 

Core Technologies Enabling Cloud-Native Data: From Containers and Kubernetes to Serverless Banking Solutions

• Containers (e.g., Docker) & Orchestration (e.g., Kubernetes): Containers package software and its dependencies into standardized units; Kubernetes automates their deployment, scaling, and management. They deploy data processing pipelines, fraud detection algorithms, and risk management tools across environments and scale efficiently to handle fluctuating workloads with container orchestration in banking.
• Microservices Architecture: Involves breaking down large, monolithic banking applications (and their underlying data systems) into smaller, independent services that communicate via APIs. It allows for targeted updates and scaling of specific functions (e.g., payment processing, customer authentication) and enables the use of diverse technologies best suited for each service.
• Serverless Computing (e.g., AWS Lambda, Azure Functions): Allows running code for specific functions without the need to provision or manage servers, forming part of serverless architectures. Banks pay only for the computing time consumed. It is ideal for event-driven data processing, such as processing incoming real-time transaction streams for fraud alerts, KYC document verification, or customer notifications.
• Managed Cloud Databases & Data Warehouses/Lakes/Lakehouses: Cloud providers offer a wide array of managed services for storing and analyzing data (e.g., Amazon S3, Azure Blob Storage for data lakes; Redshift, BigQuery, Synapse Analytics for data warehousing; Databricks for lakehouses). These services handle much of the underlying infrastructure management, patching, backups, and security configurations, allowing banks to focus on deriving value from their data.
  • Data Lake: Stores vast amounts of raw data in its native format, including structured, semi-structured, and unstructured data from various banking operations.
  • Data Warehouse: Stores structured, processed data especially for business intelligence, regulatory reporting, and performance management.
  • Data Lakehouse: Combines the flexible storage of data lakes with the structured data management and governance features of data warehouses. 

Cloud-Native vs. “Data in the Cloud” (Lift-and-Shift): Understanding True Cloud Transformation for Banks

It is crucial to understand that simply migrating existing banking databases or applications to virtual machines in the cloud (a “lift-and-shift” approach) does not inherently make them cloud-native. While this migration might offer some initial infrastructure cost savings or operational benefits, it fails to unlock the full potential of agility, true scalability, resilience, and cost-efficiency that a genuine cloud-native architecture provides. Cloud-native transformation involves re-architecting existing systems or building new applications specifically designed for the cloud environment to maximize its benefits for true cloud transformation. 

Why Cloud-Native Data is Transformative for Banking: Leveraging Banking Analytics and AI/ML in the Cloud

The unique challenges, stringent regulatory requirements, and competitive opportunities within the banking sector make cloud-native data strategies, which leverage banking analytics and AI/ML in the cloud, particularly compelling and transformative. 

• Managing Exploding and Diverse Banking Data: Data Lakes, Data Warehouses, and Cloud Storage Solutions
  • Challenge: Banks grapple with immense volumes of diverse data – customer transaction histories, account information, loan applications, investment portfolios, real-time market data feeds, anti-money laundering (AML) alerts, KYC documentation, and extensive regulatory reporting requirements.
  • Cloud-Native Solution: Object storage in data lakes can cost-effectively store petabytes of diverse financial data. Scalable computing resources can process these large datasets for complex risk modeling, customer analytics, and compliance checks. Cloud-native API gateways, built on microservices principles, can facilitate standardized and secure data exchange for Open Banking initiatives and internal system integration.
• Achieving True Interoperability & Enabling Open Banking with Cloud APIs and Secure Data Exchange
  • Challenge: Siloed legacy systems and disparate departmental databases often prevent a holistic, 360-degree view of the customer and hinder the development of seamless, integrated financial services. It also complicates compliance with Open Banking mandates.
  • Cloud-Native Solution: An API-first design philosophy and microservices architecture are inherent to many cloud-native systems. It allows disparate banking systems to communicate more effectively, enabling seamless and secure data sharing (with appropriate customer consent and robust security measures) between the bank’s applications, third-party providers (TPPs) under Open Banking regulations and regulatory bodies. It is key for Open Banking with Cloud APIs.
• Powering Advanced Banking Analytics, AI, and ML: From Fraud Detection to Personalized Customer Experiences
  • Challenge: Deriving meaningful insights from complex financial data for critical functions like real-time fraud detection, credit risk assessment, algorithmic trading, personalized financial advice, and AML pattern recognition requires significant computational power and specialized analytical tools.
  • Cloud-Native Solution: Cloud platforms provide on-demand access to powerful computing resources (CPUs, GPUs) and a rich ecosystem of managed AI/ML services. It accelerates the development, training, and deployment of sophisticated predictive models for identifying fraudulent transactions, assessing creditworthiness, optimizing investment strategies, personalizing product recommendations, and automating compliance monitoring; it powers advanced banking analytics.
• Enhancing Cloud Security in Banking and Regulatory Compliance: Addressing Data Sovereignty and Governance
  • Challenge: Protecting highly sensitive customer financial data (Personally Identifiable Information – PII, transaction details) is paramount for banks. Compliance with a complex web of regulations, including PCI DSS (Payment Card Industry Data Security Standard), AML, KYC, GDPR, CCPA, and various national financial regulations, is non-negotiable, making data sovereignty and governance critical.
  • Cloud-Native Solution: Major cloud service providers invest heavily in state-of-the-art security infrastructure and offer tools and services designed to meet stringent financial services compliance requirements (e.g., PCI DSS Level 1 certification and support for data residency). Cloud-native security typically involves a defense-in-depth strategy, incorporating fine-grained access controls, robust encryption (both in transit and at rest), comprehensive audit trails, and continuous threat monitoring. However, it is crucial to remember that the responsibility for configuring and managing these security tools correctly to meet specific banking regulations still lies with the financial institution (the shared responsibility model).
• Driving Personalized Customer Experiences and Innovative Financial Product Development with Cloud Data
  • Challenge: Customers increasingly expect personalized banking experiences, tailored financial advice, and seamless digital interactions, similar to what they receive from tech companies. Meeting these expectations with generic, one-size-fits-all products is no longer viable.
  • Cloud-Native Solution: Enables the aggregation and sophisticated analysis of data from various customer touchpoints (mobile app usage, website interactions, transaction patterns, call center logs) to gain deep insights into individual customer behavior, preferences, and financial needs. It allows banks to deliver hyper-personalized product recommendations, proactive financial guidance, customized digital interfaces, and more relevant marketing communications, significantly improving customer engagement, loyalty, and lifetime value through innovative financial product development. 

Driving Business Value: The Banking CXO’s Bottom Line with Cloud-Native Data, Cost Optimization, and Enhanced Banking Analytics

For banking CXOs, technology investments must translate directly into measurable business value and strategic advantage. Cloud-native data strategies deliver compelling returns across critical dimensions, including significant cost optimization and enhanced banking analytics. 

• Enhanced Banking Analytics and Deeper Insights for Proactive Risk Management and Sustainable Growth
  • Benefit: Move beyond basic historical reporting to predictive and prescriptive analytics. Identify emerging fraud patterns in real-time, predict credit defaults with greater accuracy, optimize capital allocation, personalize wealth management strategies, and identify new cross-selling or up-selling opportunities based on customer behavior.
  • CXO Focus: Improved risk mitigation (credit, market, operational, fraud), enhanced profitability through optimized lending and investment decisions, new revenue streams from data-driven products, and increased customer lifetime value.
• Improved Operational Excellence and Efficiency: Streamlining Banking Operations and Reducing Costs
  • Benefit: Streamline and automate core banking processes such as loan origination and approval, customer onboarding (KYC/AML checks), trade settlement, regulatory reporting, and reconciliations. Optimize resource allocation across branches and digital channels and reduce administrative overhead to improve operational efficiency.
  • CXO Focus: Significant cost savings through automation and reduced manual effort, increased staff productivity allowing focus on higher-value activities, reduced error rates, faster processing times (e.g., for loan applications), and improved overall operational agility.
• Accelerated Innovation and Agility: Competing with Fintech and Adapting to Market Changes
  • Benefit: Rapidly develop, test, and deploy new digital banking services, mobile banking applications, innovative payment solutions, and integrations with FinTech partners. Iterate quickly on product features based on customer feedback and evolving market demands.
  • CXO Focus: Enhanced customer experience leading to better acquisition and retention, increased market competitiveness against traditional banks and agile FinTech disruptors, and the ability to quickly adapt to new banking models, regulatory changes, and evolving consumer expectations for digital services.
• Better Customer Outcomes and Enhanced Digital Experience through Cloud-Powered Banking Services
  • Benefit: Deliver highly personalized financial advice and product offerings, provide more accurate and timely fraud alerts, reduce friction in customer journeys (e.g., account opening, loan applications), offer more convenient and intuitive access to banking services through preferred digital channels, and enable faster decision-making for customer requests.
  • CXO Focus: Improved customer satisfaction, loyalty, and advocacy (Net Promoter Scores), enhanced brand reputation and trust, increased share of wallet, and better adherence to financial plans and goals by customers.
• Scalability and Optimized Cost Management: Achieving Lower TCO and Financial Predictability with Cloud in Banking
  • Benefit: Pay only for the cloud resources consumed (compute, storage, networking), avoiding large upfront capital expenditures on physical hardware and data centers. Seamlessly scale infrastructure to meet fluctuating demands, such as peak transaction periods or the launch of new digital services. Leverage managed cloud services to reduce the IT operational burden associated with infrastructure maintenance, patching, and upgrades for better cost complexity management.
  • CXO Focus: Lower Total Cost of Ownership (TCO) for data infrastructure, improved Return on Investment (ROI) on IT investments, greater financial predictability and flexibility, and the ability to reallocate capital and resources from routine IT operations to strategic innovation and business growth initiatives.
• Strengthened Cloud Security Posture and Assured Regulatory Compliance for Financial Institutions
  • Benefit: Leverage the advanced, multi-layered security capabilities, certifications (e.g., PCI DSS, ISO 27001), and continuous threat intelligence offered by major cloud providers. Implement robust data governance frameworks, fine-grained access controls, and comprehensive audit trails, specifically tailored to meet stringent financial industry regulations for optimal cloud security.
  • CXO Focus: Reduced risk of costly data breaches and cyber-attacks, ensured compliance with complex financial regulations (e.g., AML, KYC, data privacy laws), maintained invaluable customer trust, and avoided of potentially severe regulatory fines and reputational damage. 

Key Considerations for a Successful Cloud-Native Data Journey and Banking Digital Transformation

Embarking on a cloud-native data strategy is a significant undertaking that requires careful planning, strategic execution, and ongoing commitment as part of your banking digital transformation. 

• Data Governance, Cloud Security in Banking, and Regulatory Compliance from the Outset: A CXO Priority
  • Action: Define clear data ownership, access policies, data lineage, and robust security protocols, specifically designed for cloud environments and financial data. Ensure end-to-end data encryption, strong identity and access management (IAM) with multi-factor authentication, and continuous security monitoring and automated alerting. Thoroughly understand and document the shared responsibility model with your chosen cloud provider(s) regarding security and regulatory compliance. Ensure all necessary regulatory attestations and contractual agreements (e.g., specific clauses for financial data handling) are in place.
• Change Management and Upskilling Your Workforce for Cloud Adoption in Financial Services
  • Action: Adopting cloud-native approaches requires new skills in areas like cloud architecture, data engineering for cloud platforms, DevOps, DevSecOps, and AI/ML specific to financial services. Invest proactively in comprehensive training programs and industry certifications and potentially hire new talent with specialized cloud expertise. Foster a culture of continuous learning, agility, and close collaboration between IT, data science, cybersecurity, risk management, compliance, and core business units. It addresses cultural and organizational resistance and cloud-specific skill gaps.
• Strategic Vendor Selection and Partnerships for Your Banking Cloud Strategy and Fintech Integration
  • Action: Carefully evaluate cloud service providers based on their financial services-specific offerings, compliance certifications (e.g., PCI DSS, SOC 2, ISO 27017/27018), data residency options, security track record, service level agreements (SLAs), pricing models, and their ecosystem of financial technology partners. Consider multi-cloud or hybrid cloud strategies if they align with your bank’s risk appetite, regulatory constraints, or data sovereignty requirements.
• Developing a Phased Roadmap and Prioritization for Cloud Data Migration and Modernization in Banks
  • Action: Avoid a “big bang” approach. Start with well-defined pilot projects that address specific high-impact pain points or offer clear, measurable value (e.g., enhancing fraud detection capabilities for a specific payment channel, developing a customer segmentation model for a new product launch). Learn from these initial projects and iterate. Develop a clear, phased roadmap that aligns with your bank’s overall strategic objectives, such as digital transformation, operational efficiency improvements, or enhanced risk management, including data migration. Identify key data domains (e.g., customer data, transaction data, risk data) and use cases to prioritize for cloud-native adoption.
• Data Integration and Interoperability Planning: Bridging Legacy Systems with Cloud-Native Banking
  • Action: Develop a comprehensive strategy for integrating data from existing legacy systems (e.g., core banking platforms, mainframes) with new cloud-native platforms and applications. Prioritize the adoption of modern data integration patterns and industry standards like APIs (e.g., for Open Banking, internal microservices communication) to ensure future-proof interoperability and data fluidity across the organization.
• Cloud Cost Optimization and Financial Management in Banking Cloud Environments
  • Action: While the cloud offers significant cost benefits through pay-as-you-go models, unmonitored or poorly managed usage can lead to unexpected and escalating expenses. Implement robust cost management tools, establish clear tagging strategies for resource allocation and tracking, set budgets and alerts, and conduct regular reviews of cloud spending to optimize consumption and ensure cost efficiency. Explore reserved instances or savings plans for predictable workloads to further reduce costs, addressing overall cost complexity. 

The Future is Cloud-Native: AI in Banking, Real-Time Analytics, and the Next Wave of Financial Innovation

The adoption of cloud-native data principles is not merely a current trend; it is the fundamental bedrock for future innovation, competitiveness, and resilience in the banking industry, heavily featuring AI in banking and real-time analytics. 

• Federated Learning for Enhanced Financial Crime Prevention and Secure Data Collaboration
  • Training sophisticated AI models across multiple financial institutions or jurisdictions without centralizing or directly exposing sensitive raw customer data. This collaborative approach can significantly improve the detection of complex fraud schemes and money laundering activities while preserving data privacy and adhering to cross-border data-sharing regulations.
• Real-time Banking Analytics at Scale for Proactive Fraud Detection and Personalized Offers
  • Gaining instant insights from high-velocity streaming data, such as real-time transaction feeds, market data, and customer digital interactions. It enables proactive fraud intervention, immediate personalized offers or alerts, dynamic risk scoring, and truly responsive customer service.
• AI-Driven Financial Advisory and Intelligent Automation: The Future of Personalized Banking
  • Cloud-native platforms provide the immense storage and computational power needed to develop and deploy advanced AI algorithms for hyper-personalized financial advice, automated wealth management (Robo-advisory), intelligent document processing (e.g., for loan applications or KYC), and advanced chatbots for customer service.
• Generative AI in Banking: Transforming Customer Service, Operations, and Product Development
  • Emerging applications of generative AI, such as AI-assisted code generation for faster application development, automated creation of regulatory reports, generation of synthetic data for robust system testing and model training (while protecting real customer data), and sophisticated fraud pattern simulation will heavily rely on the scalable, flexible, and data-rich backbones provided by cloud-native architectures. 

Conclusion: Embracing the Cloud-Native Future for Banking Excellence, Digital Transformation, and Competitive Advantage

For banking CXOs, embracing a comprehensive cloud-native data strategy is a profound strategic imperative, fundamental to transforming how your financial institution leverages data for banking excellence and digital transformation. This journey requires a clear vision, meticulous planning, and unwavering commitment, promising a more agile, intelligent, secure, compliant, and customer-centric future with a significant competitive advantage. Key considerations and actions include: 

• Enhancing Customer Relationships: Utilizing data to personalize experiences and deepen engagement.
• Strengthening Risk Management: Leveraging cloud capabilities for more robust and predictive risk models.
• Improving Operational Efficiency: Streamlining processes and reducing costs through cloud-native architectures.
• Ensuring Regulatory Compliance: Meeting evolving regulatory demands with enhanced data governance and reporting.
• Driving Sustainable Innovation: Fostering a data-driven culture to develop new products and services.
• Strategic Implementation: Asking critical questions, fostering internal alignment, and taking deliberate steps to unlock data’s immense business value securely and efficiently in the cloud. 

Partner with Veltris: Navigating Your Cloud-Native Data Transformation, Banking Analytics, and AI Implementation in Banking

Understanding the core concepts of cloud-native data is the crucial first step. Successfully implementing these strategies to drive tangible business value and navigate the complex regulatory landscape of the banking sector requires specialized expertise, deep domain knowledge, and a trusted partner, such as Veltris which includes expertise in banking analytics and AI implementation.  

Veltris empowers banking and financial services organizations to harness the full potential of cloud-native data. Our profound understanding of the banking domain, including its unique regulatory pressures (such as PCI DSS, AML, KYC, and Open Banking mandates) and operational challenges, combined with our cutting-edge expertise in cloud technologies (AWS, Azure, GCP), data engineering, advanced analytics, and AI/ML, makes us an ideal partner for your digital transformation journey. 

How Veltris Can Accelerate Your Cloud-Native Data Initiatives, Fintech Security, and Regulatory Compliance in Banking: 

• Strategic Cloud Advisory for Financial Services: We help you define a clear and compliant cloud-native data strategy aligned with your specific business objectives, ensuring optimal TCO, ROI, and adherence to banking regulations. We assess your current data landscape, including legacy core banking systems, and develop a tailored roadmap for modernization and migration to the cloud. This includes addressing Fintech security concerns.
• Modern Data Architecture & Engineering for Banks: Veltris designs and builds scalable, resilient, and secure cloud-native data platforms – including data lakes, Lakehouses, and warehouses – specifically architected for banking needs on leading cloud providers. We ensure your data architecture is optimized for performance, cost, security, and future growth, capable of handling diverse financial data types and analytical workloads.
• Advanced Analytics & AI/ML Solutions for Fraud, Risk, and Customer Insights: Unlock actionable intelligence from your financial data with our expertise in developing and deploying sophisticated AI/ML models for real-time fraud detection and prevention, credit risk scoring, AML pattern recognition, customer segmentation for personalized marketing, and operational efficiency improvements.
• Open Banking & API Integration: We navigate the complexities of Open Banking standards and financial data exchange protocols, helping you achieve seamless and secure data sharing, develop robust API strategies, and foster a connected banking ecosystem in compliance with regulations like PSD2.
• Regulatory Compliance and Security for Financial Data (PCI DSS, AML, KYC): Veltris prioritizes data security and regulatory compliance. We help you design and implement robust security controls, data governance frameworks, and audit trails to protect sensitive financial information (PFI) and meet stringent regulatory requirements (e.g., PCI DSS, GDPR, CCPA, SOX) within your cloud environment.
• DevSecOps & MLOps for Agile Banking: We enable agility and accelerate innovation by implementing DevSecOps (Development, Security, and Operations) and MLOps (Machine Learning Operations) practices, streamlining the secure development, deployment, and management of your data pipelines, analytical applications, and AI/ML models in the banking context.
• Managed Cloud Services & Optimization for Banking Systems: Beyond initial implementation, Veltris can provide ongoing management and optimization of your cloud-native data infrastructure, ensuring it remains performant, cost-effective, secure, compliant, and aligned with your evolving business and regulatory needs. 

At Veltris, we understand that a successful cloud-native data strategy is pivotal for Banking CXOs aiming to enhance analytics, fortify risk management, achieve operational excellence, and deliver superior customer experiences. We are committed to partnering with you to transform your data into a strategic asset that improves customer outcomes, mitigates risk, ensures compliance, and drives sustainable growth in the competitive banking landscape. 

Ready to explore how Veltris can support your banking organization’s cloud-native data journey? Contact us today to start the conversation. 

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